>> Good day, everyone. Thank you for joining me. I'm Cindy Maike, joined by Rick Taylor of Cloudera. We're here to talk about predictive maintenance for the public sector and how to increase asset service reliability. On today's agenda, we'll talk specifically around how to optimize your equipment maintenance, how to reduce costs, asset failure with data and analytics. We'll go into a little more depth on what type of data, the analytical methods that we're typically seeing used, the associated- Brooke will go over a case study as well as a reference architecture. So by basic definition, predictive maintenance is about determining when an asset should be maintained and what specific maintenance activities need to be performed either based upon an assets actual condition or state. It's also about predicting and preventing failures and performing maintenance on your time on your schedule to avoid costly unplanned downtime. McKenzie has looked at analyzing predictive maintenance costs across multiple industries and has identified that there's the opportunity to reduce overall predictive maintenance costs by roughly 50% with different types of analytical methods. So let's look at those three types of models. First, we've got our traditional type of method for maintenance, and that's really about uncorrective maintenance, and that's when we're performing maintenance on an asset after the equipment fails. The challenges with that is we end up with unplanned downtime. We end up with disruptions in our schedules, as well as reduce quality around the performance of the asset. And then we started looking at preventive maintenance and preventative maintenance is really when we're performing maintenance on a set schedule. The challenges with that is we're typically doing it regardless of the actual condition of the asset, which has resulted in unnecessary downtime and expense. And specifically we're really now focused on condition-based maintenance, which is looking at leveraging predictive maintenance techniques based upon actual conditions and real time events and processes. Within that, we've seen organizations and again, source from McKenzie, have a 50% reduction in downtime, as well as overall 40% reduction in maintenance costs. Again, this is really looking at things across multiple industries, but let's look at it in the context of the public sector and based upon some activity by the department of energy several years ago, they really looked at what does predictive maintenance mean to the public sector? What is the benefit of looking at increasing return on investment of assets, reducing, you know, reduction in downtime as well as overall maintenance costs. So corrective or reactive based maintenance is really about performing once there's been a failure and then the movement towards preventative, which is based upon a set schedule. We're looking at predictive where we're monitoring real-time conditions. And most importantly is now actually leveraging IOT and data and analytics to further reduce those overall down times. And there's a research report by the department of energy that goes into more specifics on the opportunity within the public sector. So Rick, let's talk a little bit about what are some of the challenges regarding data, regarding predictive maintenance? >> Some of the challenges include having data silos, historically our government organizations and organizations in the commercial space as well, have multiple data silos. They've spun up over time. There are multiple business units and note, there's no single view of assets. And oftentimes there's redundant information stored in these silos of information. Couple that with huge increases in data volume, data growing exponentially, along with new types of data that we can ingest there's social media, there's semi and unstructured data sources and the real time data that we can now collect from the internet of things. And so the challenge is to collect all these assets together and begin to extract intelligence from them and additional insights and and that in turn, then fuels machine learning and what we call artificial intelligence, which enables predictive maintenance. Next slide. >> Cindy: So let's look specifically at, you know, the types of use cases and I'm going to- Rick and I are going to focus on those use cases, where do we see predictive maintenance coming in to the procurement facility, supply chain, operations and logistics? We've got various level of maturity. So, you know, we're talking about predictive maintenance. We're also talking about using information, whether it be on a connected asset or a vehicle doing monitoring to also leveraging predictive maintenance on how do we bring about looking at data from connected warehouses facilities and buildings? I'll bring an opportunity to both increase the quality and effectiveness of the missions within the agencies to also looking at looking at cost efficiency, as well as looking at risk and safety. And the types of data, you know, that Rick mentioned around, you know, the new types of information. Some of those data elements that we typically have seen is looking at failure history. So when has an asset or a machine or a component within a machine failed in the past? We've also looking at bringing together a maintenance history, looking at a specific machine. Are we getting error codes off of a machine or assets looking at when we've replaced certain components to looking at how are we actually leveraging the assets? What were the operating conditions? Pulling up data from a sensor on that asset? Also looking at the features of an asset, whether it's, you know, engine size it's make and model, where's the asset located? To also looking at who's operated the asset, you know, whether it be their certifications, what's their experience, how are they leveraging the assets? And then also bringing in together some of the pattern analysis that we've seen. So what are the operating limits? Are we getting service reliability? Are we getting a product recall information from the actual manufacturer? So Rick, I know the data landscape has really changed. Let's, let's go over looking at some of those components. >> Rick: Sure. So this slide depicts sort of the, some of the inputs that inform a predictive maintenance program. So we've talked a little bit about the silos of information, the ERP system of record, perhaps the spares and the service history. So we want, what we want to do is combine that information with sensor data, whether it's a facility and equipment sensors, or temperature and humidity, for example. All this stuff is then combined together and then used to develop machine learning models that better inform predictive maintenance, because we do need to take into account the environmental factors that may cause additional wear and tear on the asset that we're monitoring. So here are some examples of private sector maintenance use cases that also have broad applicability across the government. For example, one of the busiest airports in Europe is running Cloudera on Azure to capture secure and correlate sensor data collected from equipment within the airport. The people moving equipment more specifically, the escalators, the elevators, and the baggage carousels. The objective here is to prevent breakdowns and improve airport efficiency and passenger safety. Another example is a container shipping port. In this case, we use IOT data and machine learning to help customers recognize how their cargo handling equipment is performing in different weather conditions to understand how usage relates to failure rates and to detect anomalies in transport systems. These all improve port efficiency. Another example is Navistar. Navistar is a leading manufacturer of commercial trucks, buses, and military vehicles. Typically vehicle maintenance, as Cindy mentioned, is based on miles traveled or based on a schedule or a time since the last service. But these are only two of the thousands of data points that can signal the need for maintenance. And as it turns out, unscheduled maintenance and vehicle breakdowns account for a large share of the total cost for vehicle owners. So to help fleet owners move from a reactive approach to a more predictive model, Navistar built an IOT enabled remote diagnostics platform called On Command. The platform brings in over 70 sensor data feeds for more than 375,000 connected vehicles. These include engine performance, trucks speed, acceleration, coolant temperature and break ware. This data is then correlated with other Navistar and third-party data sources, including weather, geolocation, vehicle usage, traffic, warranty, and parts inventory information. So the platform then uses machine learning and advanced analytics to automatically detect problems early and predict maintenance requirements. So how does the fleet operator use this information? They can monitor truck health and performance from smartphones or tablets and prioritize needed repairs. Also, they can identify that the nearest service location that has the relevant parts, the train technicians and the available service space. So sort of wrapping up the benefits. Navistar's helped fleet owners reduce maintenance costs by more than 30%. This same platform has also used to help school buses run safely and on time. For example, one school district with 110 buses that travel over a million miles annually reduce the number of tows needed year over year, thanks to predictive insights, delivered by this platform. So I'd like to take a moment and walk through the data life cycle as depicted in this diagram. So data ingest from the edge may include feeds from the factory floor or things like connected vehicles, whether they're trucks, aircraft, heavy equipment, cargo vessels, et cetera. Next, the data lands on a secure and governed data platform where it is combined with data from existing systems of record to provide additional insights. And this platform supports multiple analytic functions working together on the same data while maintaining strict security, governance and control measures. Once processed the data is used to train machine learning models, which are then deployed into production, monitored and retrained as needed to maintain accuracy. The process data is also typically placed in a data warehouse and use to support business intelligence analytics and dashboards. And in fact, this data life cycle is representative of one of our government customers doing condition-based maintenance across a variety of aircraft. And the benefits they've discovered include; less unscheduled maintenance and a reduction in mean man hours to repair, increased maintenance efficiencies, improved aircraft availability, and the ability to avoid cascading component failures, which typically costs more in repair cost and downtime. Also, they're able to better forecast the requirements for replacement parts and consumables and last, and certainly very importantly, this leads to enhanced safety. This chart overlays the secure open source Cloudera platform used in support of the data life cycle we've been discussing. Cloudera data flow, provides the data ingest, data movement and real time streaming data query capabilities. So data flow gives us the capability to bring data in from the asset of interest, from the internet of things. While the data platform provides a secure governed data lake and visibility across the full machine learning life cycle eliminates silos and streamlines workflows across teams. The platform includes a integrated suite of secure analytic applications. And two that we're specifically calling out here are Cloudera machine learning, which supports the collaborative data science and machine learning environment, which facilitates machine learning and AI and the Cloudera data warehouse, which supports the analytics and business intelligence, including those dashboards for leadership Cindy, over to you. >> Cindy: Rick, Thank you. And I hope that Rick and I provided you some insights on how predictive maintenance condition-based maintenance is being used and can be used within your respective agency, bringing together data sources that maybe you're having challenges with today, bringing that more real-time information in from a streaming perspective, blending that industrial IOT, as well as historical information together to help actually optimize maintenance and produce costs within each of your agencies. To learn a little bit more about Cloudera and our, what we're doing from a predictive maintenance, please visit us at Cloudera.com/Solutions/PublicSector And we look forward to scheduling a meeting with you. And on that, we appreciate your time today and thank you very much.

>>Hi, this is Cindy Mikey, vice president of industry solutions at caldera. Joining me today is chef is Molly, our solution engineer for the public sector. Today. We're going to talk about speed to insight. Why using machine learning in the public sector, specifically around fraud, waste and abuse. So topic for today, we'll discuss machine learning, why the public sector uses it to target fraud, waste, and abuse, the challenges. How do we enhance your data and analytical approaches the data landscape analytical methods and shad we'll go over reference architecture and a case study. So by definition at fraud waste and abuse per the government accountability office is broad as an attempt to obtain something about a value through unwelcomed misrepresentation waste is about squandering money or resources and abuse is about behaving improperly or unreasonably to actually obtain something of value for your personal, uh, benefit. So as we look at fraud, um, and across all industries, it's a top of mind, um, area within the public sector. >>Um, the types of fraud that we see is specifically around cyber crime, uh, looking at accounting fraud, whether it be from an individual perspective to also, uh, within organizations, looking at financial statement fraud, to also looking at bribery and corruption, as we look at fraud, it really hits us from all angles, whether it be from external perpetrators or internal perpetrators, and specifically for the research by PWC, the key focus area is we also see over half of fraud is actually through some form of internal or external perpetrators, again, key topics. So as we also look at a report recently by the association of certified fraud examiners, um, within the public sector, the us government, um, in 2017, it was identified roughly $148 billion was attributable to fraud, waste and abuse. Specifically of that 57 billion was focused on reported monetary losses and another 91 billion on areas where that opportunity or the monetary basis had not yet been measured. >>As we look at breaking those areas down again, we look at several different topics from an out payment perspective. So breaking it down within the health system, over $65 billion within social services, over $51 billion to procurement fraud to also, uh, uh, fraud, waste and abuse that's happening in the grants and the loan process to payroll fraud, and then other aspects, again, quite a few different topical areas. So as we look at those areas, what are the areas that we see additional type of focus, those are broad stroke areas. What are the actual use cases that, um, agencies are using the data landscape? What data, what analytical methods can we use to actually help curtail and prevent some of the, uh, the fraud waste and abuse. So, as we look at some of the analytical processes and analytical use great, uh, use cases in the public sector, whether it's from, uh, you know, the taxation areas to looking at, you know, social services, uh, to public safety, to also the, um, our, um, additional agency methods, we're going to focus specifically on some of the use cases around, um, you know, fraud within the tax area. >>Uh, we'll briefly look at some of the aspects of unemployment insurance fraud, uh, benefit fraud, as well as payment integrity. So fraud has its, um, uh, underpinnings in quite a few different government agencies and difficult, different analytical methods and I usage of different data. So I think one of the key elements is, you know, you can look at your, your data landscape on specific data sources that you need, but it's really about bringing together different data sources across a different variety, a different velocity. So, uh, data has different dimensions. So we'll look at on structured types of data of semi-structured data, behavioral data, as well as when we look at, um, you know, predictive models, we're typically looking at historical type information, but if we're actually trying to look at preventing fraud before it actually happens, or when a case may be in flight, which is specifically a use case that Chev is going to talk about later it's how do I look at more, that real, that streaming information? >>How do I take advantage of data, whether it be, uh, you know, uh, financial transactions we're looking at, um, asset verification, we're looking at tax records, we're looking at corporate filings. Um, and we can also look at more, uh, advanced data sources where as we're looking at, um, investigation type information. So we're maybe going out and we're looking at, uh, deep learning type models around, uh, you know, semi or that, uh, behavioral that's unstructured data, whether it be camera analysis and so forth. So for quite a different variety of data and the breadth and the opportunity really comes about when you can integrate and look at data across all different data sources. So in essence, looking at a more extensive, uh, data landscape. So specifically I want to focus on some of the methods, some of the data sources and some of the analytical techniques that we're seeing, uh, being used, um, in the government agencies, as well as opportunities to look at new methods. >>So as we're looking at, you know, from a, um, an audit planning or looking at, uh, the opportunity for the likelihood of non-compliance, um, specifically we'll see data sources where we're maybe looking at a constituents profile, we might actually be investigating the forms that they provided. We might be comparing that data, um, or leveraging internal data sources, possibly looking at net worth, comparing it against other financial data, and also comparison across other constituents groups. Some of the techniques that we use are some of the basic natural language processing, maybe we're going to do some text mining. We might be doing some probabilistic modeling, uh, where we're actually looking at, um, information within the agency to also comparing that against possibly tax forms. A lot of times it's information historically has been done on a batch perspective, both structured and semi-structured type information. And typically the data volumes can be low, but we're also seeing those data volumes on increase exponentially based upon the types of events that we're dealing with, the number of transactions. >>Um, so getting the throughput, um, and chef's going to specifically talk about that in a moment. The other aspect is, as we look at other areas of opportunity is when we're building upon, how do I actually do compliance? How do I actually look at conducting audits or potential fraud to also looking at areas of under-reported tax information? So there you might be pulling in, um, some of our other types of data sources, whether it's being property records, it could be data that's being supplied by the actual constituents or by vendors to also pulling in social media information to geographical information, to leveraging photos on techniques that we're seeing used is possibly some sentiment analysis, link analysis. Um, how do we actually blend those data sources together from a natural language processing? But I think what's important here is also the method and the looking at the data velocity, whether it be batch, whether it be near real time, again, looking at all types of data, whether it's structured semi-structured or unstructured and the key and the value behind this is, um, how do we actually look at increasing the potential revenue or the, uh, under reported revenue? >>Uh, how do we actually look at stopping fraudulent payments before they actually occur? Um, also looking at increasing the amount of, uh, the level of compliance, um, and also looking at the potential of prosecution of fraud cases. And additionally, other areas of opportunity could be looking at, um, economic planning. How do we actually perform some link analysis? How do we bring some more of those things that we saw in the data landscape on customer, or, you know, constituent interaction, bringing in social media, bringing in, uh, potentially police records, property records, um, other tax department, database information. Um, and then also looking at comparing one individual to other individuals, looking at people like a specific constituent, are there areas where we're seeing, uh, um, other aspects of a fraud potentially being occurring. Um, and also as we move forward, some of the more advanced techniques that we're seeing around deep learning is looking at computer vision, um, leveraging geospatial information, looking at social network entity analysis, uh, also looking at, um, agent-based modeling techniques, where we're looking at, uh, simulation Monte Carlo type techniques that we typically see in the financial services industry, actually applying that to fraud, waste, and abuse within the, uh, the public sector. >>Um, and again, that really lends itself to a new opportunities. And on that, I'm going to turn it over to Shev to talk about, uh, the reference architecture for, uh, doing these baskets. >>Thanks, Cindy. Um, so I'm going to walk you through an example, reference architecture for fraud detection using, uh, Cloudera underlying technology. Um, and you know, before I get into the technical details, uh, I want to talk about how this would be implemented at a much higher level. So with fraud detection, what we're trying to do is identify anomalies or novelists behavior within our data sets. Um, now in order to understand what aspects of our incoming data represents anomalous behavior, we first need to understand what normal behavior is. So in essence, once we understand normal behavior, anything that deviates from it can be thought of as an anomaly, right? So in order to understand what normal behavior is, we're going to need to be able to collect store and process a very large amount of historical data. And so then comes clutter's platform and this reference architecture that needs to before you, so, uh, let's start on the left-hand side of this reference architecture with the collect phase. >>So fraud detection will always begin with data collection. Uh, we need to collect large amounts of information from systems that could be in the cloud. It could be in the data center or even on edge devices, and this data needs to be collected so we can create our normal behavior profiles. And these normal behavioral profiles would then in turn, be used to create our predictive models for fraudulent activity. Now, uh, uh, to the data collection side, one of the main challenges that many organizations face, uh, in this phase, uh, involves using a single technology that can handle, uh, data that's coming in all different types of formats and protocols and standards with different porosities and velocities. Um, let me give you an example. Uh, we could be collecting data from a database that gets updated daily, uh, and maybe that data is being collected in Agra format. >>At the same time, we can be collecting data from an edge device that's streaming in every second, and that data may be coming in Jason or a binary format, right? So this is a data collection challenge that can be solved with clutter data flow, which is a suite of technologies built on Apache NIFA and mini five, allowing us to ingest all of this data, do a drag and drop interface. So now we're collecting all of this data, that's required to map out normal behavior. The next thing that we need to do is enrich it, transform it and distribute it to, uh, you know, downstream systems for further process. Uh, so let's, let's walk through how that would work first. Let's taking Richmond for, uh, for enrichment, think of adding additional information to your incoming data, right? Let's take, uh, financial transactions, for example, uh, because Cindy mentioned it earlier, right? >>You can store known locations of an individual in an operational database, uh, with Cloudera that would be HBase. And as an individual makes a new transaction, their geo location that's in that transaction data, it can be enriched with previously known locations of that very same individual and all of that enriched data. It can be later used downstream for predictive analysis, predictable. So the data has been enrich. Uh, now it needs to be transformed. We want the data that's coming in, uh, you know, Avro and Jason and binary and whatever other format to be transformed into a single common format. So it can be used downstream for stream processing. Uh, again, this is going to be done through clutter and data flow, which is backed by NIFA, right? So the transformed semantic data is then going to be stimulated to Kafka and coffin. It's going to serve as that central repository of syndicated services or a buffer zone, right? >>So cough is, you know, pretty much provides you with, uh, extremely fast resilient and fault tolerance storage. And it's also going to give you the consumer APIs that you need that are going to enable a wide variety of applications to leverage that enriched and transformed data within your buffer zone. Uh, I'll add that, you know, 17, so you can store that data, uh, in a distributed file system, give you that historical context that you're going to need later on for machine learning, right? So the next step in the architecture is to leverage a cluttered SQL string builder, which enables us to write, uh, streaming sequel jobs on top of Apache Flink. So we can, uh, filter, analyze and, uh, understand the data that's in the Kafka buffer zone in real time. Uh I'll you know, I'll also add like, you know, if you have time series data, or if you need a lab type of cubing, you can leverage kudu, uh, while EDA or exploratory data analysis and visualization, uh, can all be enabled through clever visual patient technology. >>All right, so we've filtered, we've analyzed and we've explored our incoming data. We can now proceed to train our machine learning models, uh, which will detect anomalous behavior in our historically collected data set, uh, to do this, we can use a combination of supervised unsupervised, uh, even deep learning techniques with neural networks and these models can be tested on new incoming streaming data. And once we've gone ahead and obtain the accuracy of the performance, the scores that we want, we can then take these models and deploy them into production. And once the models are productionalized or operationalized, they can be leveraged within our streaming pipeline. So as new data is ingested in real-time knife, I can query these models to detect if the activity is anomalous or fraudulent. And if it is, they can alert downstream users and systems, right? So this in essence is how fraudulent activity detection works. >>Uh, and this entire pipeline is powered by clutter's technology, right? And so, uh, the IRS is one of, uh, clutters customers. That's leveraging our platform today and implementing, uh, a very similar architecture, uh, to detect fraud, waste, and abuse across a very large set of, uh, historical facts, data. Um, and one of the neat things with the IRS is that they've actually, uh, recently leveraged the partnership between Cloudera and Nvidia to accelerate their Spark-based analytics and their machine learning. Uh, and the results have been nothing short of amazing, right? And in fact, we have a quote here from Joe and salty who's, uh, you know, the technical branch chief for the research analytics and statistics division group within the IRS with zero changes to our fraud detection workflow, we're able to obtain eight times to performance simply by adding GPS to our mainstream big data servers. This improvement translates to half the cost of ownership for the same workloads, right? So embedding GPU's into the reference architecture I covered earlier has enabled the IRS to improve their time to insights by as much as eight X while simultaneously reducing their underlying infrastructure costs by half, uh, Cindy back to you >>Chef. Thank you. Um, and I hope that you found, uh, some of the, the analysis, the information that Sheva and I have provided, um, to give you some insights on how cloud era is actually helping, uh, with the fraud waste and abuse challenges within the, uh, the public sector, um, specifically looking at any and all types of data, how the clutter a platform is bringing together and analyzing information, whether it be you're structured you're semi-structured to unstructured data, both in a fast or in a real time perspective, looking at anomalies, being able to do some of those on detection methods, uh, looking at neural network analysis, time series information. So next steps we'd love to have an additional conversation with you. You can also find on some additional information around, uh, how quad areas working in the federal government by going to cloudera.com solutions slash public sector. And we welcome scheduling a meeting with you again, thank you for joining Chevy and I today, we greatly appreciate your time and look forward to future >>Conversation..

>>Hi, this is Cindy Mikey, vice president of industry solutions at caldera. Joining me today is chef is Molly, our solution engineer for the public sector. Today. We're going to talk about speed to insight. Why using machine learning in the public sector, specifically around fraud, waste and abuse. So topic for today, we'll discuss machine learning, why the public sector uses it to target fraud, waste, and abuse, the challenges. How do we enhance your data and analytical approaches the data landscape analytical methods and shad we'll go over reference architecture and a case study. So by definition, fraud, waste and abuse per the government accountability office is fraud. Isn't an attempt to obtain something about value through unwelcome misrepresentation waste is about squandering money or resources and abuse is about behaving improperly or unreasonably to actually obtain something of value for your personal benefit. So as we look at fraud, um, and across all industries, it's a top of mind, um, area within the public sector. >>Um, the types of fraud that we see is specifically around cyber crime, uh, looking at accounting fraud, whether it be from an individual perspective to also, uh, within organizations, looking at financial statement fraud, to also looking at bribery and corruption, as we look at fraud, it really hits us from all angles, whether it be from external perpetrators or internal perpetrators, and specifically from the research by PWC, the key focus area is we also see over half of fraud is actually through some form of internal or external, uh, perpetrators again, key topics. So as we also look at a report recently by the association of certified fraud examiners, um, within the public sector, the us government, um, in 2017, it was identified roughly $148 billion was attributable to fraud, waste and abuse. Specifically about 57 billion was focused on reported monetary losses and another 91 billion on areas where that opportunity or the monetary basis had not yet been measured. >>As we look at breaking those areas down again, we look at several different topics from permit out payment perspective. So breaking it down within the health system, over $65 billion within social services, over $51 billion to procurement fraud to also, um, uh, fraud, waste and abuse that's happening in the grants and the loan process to payroll fraud, and then other aspects, again, quite a few different topical areas. So as we look at those areas, what are the areas that we see additional type of focus, there's a broad stroke areas. What are the actual use cases that our agencies are using the data landscape? What data, what analytical methods can we use to actually help curtail and prevent some of the, uh, the fraud waste and abuse. So, as we look at some of the analytical processes and analytical use crate, uh, use cases in the public sector, whether it's from, uh, you know, the taxation areas to looking at, you know, social services, uh, to public safety, to also the, um, our, um, uh, additional agency methods, we're gonna use focused specifically on some of the use cases around, um, you know, fraud within the tax area. >>Uh, we'll briefly look at some of the aspects of, um, unemployment insurance fraud, uh, benefit fraud, as well as payment and integrity. So fraud has it it's, um, uh, underpinnings inquiry, like you different on government agencies and difficult, different analytical methods, and I usage of different data. So I think one of the key elements is, you know, you can look at your, your data landscape on specific data sources that you need, but it's really about bringing together different data sources across a different variety, a different velocity. So, uh, data has different dimensions. So we'll look at structured types of data of semi-structured data, behavioral data, as well as when we look at, um, you know, predictive models. We're typically looking at historical type information, but if we're actually trying to look at preventing fraud before it actually happens, or when a case may be in flight, which is specifically a use case that shad is going to talk about later is how do I look at more of that? >>Real-time that streaming information? How do I take advantage of data, whether it be, uh, you know, uh, financial transactions we're looking at, um, asset verification, we're looking at tax records, we're looking at corporate filings. Um, and we can also look at more, uh, advanced data sources where as we're looking at, um, investigation type information. So we're maybe going out and we're looking at, uh, deep learning type models around, uh, you know, semi or that, uh, behavioral, uh, that's unstructured data, whether it be camera analysis and so forth. So for quite a different variety of data and the, the breadth and the opportunity really comes about when you can integrate and look at data across all different data sources. So in a looking at a more extensive, uh, data landscape. So specifically I want to focus on some of the methods, some of the data sources and some of the analytical techniques that we're seeing, uh, being used, um, in the government agencies, as well as opportunities, uh, to look at new methods. >>So as we're looking at, you know, from a, um, an audit planning or looking at, uh, the opportunity for the likelihood of non-compliance, um, specifically we'll see data sources where we're maybe looking at a constituents profile, we might actually be investigating the forms that they've provided. We might be comparing that data, um, or leveraging internal data sources, possibly looking at net worth, comparing it against other financial data, and also comparison across other constituents groups. Some of the techniques that we use are some of the basic natural language processing, maybe we're going to do some text mining. We might be doing some probabilistic modeling, uh, where we're actually looking at, um, information within the agency to also comparing that against possibly tax forms. A lot of times it's information historically has been done on a batch perspective, both structured and semi-structured type information. And typically the data volumes can be low, but we're also seeing those data volumes on increase exponentially based upon the types of events that we're dealing with, the number of transactions. >>Um, so getting the throughput, um, and chef's going to specifically talk about that in a moment. The other aspect is, as we look at other areas of opportunity is when we're building upon, how do I actually do compliance? How do I actually look at conducting audits, uh, or potential fraud to also looking at areas of under-reported tax information? So there you might be pulling in some of our other types of data sources, whether it's being property records, it could be data that's being supplied by the actual constituents or by vendors to also pulling in social media information to geographical information, to leveraging photos on techniques that we're seeing used is possibly some sentiment analysis, link analysis. Um, how do we actually blend those data sources together from a natural language processing? But I think what's important here is also the method and the looking at the data velocity, whether it be batch, whether it be near real time, again, looking at all types of data, whether it's structured semi-structured or unstructured and the key and the value behind this is, um, how do we actually look at increasing the potential revenue or the, um, under reported revenue? >>Uh, how do we actually look at stopping fraudulent payments before they actually occur? Um, also looking at increasing the amount of, uh, the level of compliance, um, and also looking at the potential of prosecution of fraud cases. And additionally, other areas of opportunity could be looking at, um, economic planning. How do we actually perform some link analysis? How do we bring some more of those things that we saw in the data landscape on customer, or, you know, constituent interaction, bringing in social media, bringing in, uh, potentially police records, property records, um, other tax department, database information. Um, and then also looking at comparing one individual to other individuals, looking at people like a specific, like a constituent, are there areas where we're seeing, uh, >>Um, other >>Aspects of, of fraud potentially being occurring. Um, and also as we move forward, some of the more advanced techniques that we're seeing around deep learning is looking at computer vision, um, leveraging geospatial information, looking at social network entity analysis, uh, also looking at, uh, agent-based modeling techniques, where we're looking at simulation Monte Carlo type techniques that we typically see in the financial services industry, actually applying that to fraud, waste, and abuse within the, uh, the public sector. Um, and again, that really, uh, lends itself to a new opportunities. And on that, I'm going to turn it over to chef to talk about, uh, the reference architecture for, uh, doing these buckets. >>Thanks, Cindy. Um, so I'm gonna walk you through an example, reference architecture for fraud detection using, uh, Cloudera's underlying technology. Um, and you know, before I get into the technical details, uh, I want to talk about how this would be implemented at a much higher level. So with fraud detection, what we're trying to do is identify anomalies or novelists behavior within our datasets. Um, now in order to understand what aspects of our incoming data represents anomalous behavior, we first need to understand what normal behavior is. So in essence, once we understand normal behavior, anything that deviates from it can be thought of as an anomaly, right? So in order to understand what normal behavior is, we're going to need to be able to collect store and process a very large amount of historical data. And so incomes, clutters platform, and this reference architecture that needs to be for you. >>So, uh, let's start on the left-hand side of this reference architecture with the collect phase. So fraud detection will always begin with data collection. We need to collect large amounts of information from systems that could be in the cloud. It could be in the data center or even on edge devices, and this data needs to be collected so we can create our normal behavior profiles. And these normal behavioral profiles would then in turn, be used to create our predictive models for fraudulent activity. Now, uh, thinking, uh, to the data collection side, one of the main challenges that many organizations face, uh, in this phase, uh, involves using a single technology that can handle, uh, data that's coming in all different types of formats and protocols and standards with different velocities and velocities. Um, let me give you an example. Uh, we could be collecting data from a database that gets updated daily, uh, and maybe that data is being collected in Agra format. >>At the same time, we can be collecting data from an edge device that's streaming in every second, and that data may be coming in Jason or a binary format, right? So this is a data collection challenge that can be solved with cluttered data flow, which is a suite of technologies built on a patch NIFA in mini five, allowing us to ingest all of this data, do a drag and drop interface. So now we're collecting all of this data, that's required to map out normal behavior. The next thing that we need to do is enrich it, transform it and distribute it to, uh, you know, downstream systems for further process. Uh, so let's, let's walk through how that would work first. Let's taking Richmond for, uh, for enrichment, think of adding additional information to your incoming data, right? Let's take, uh, financial transactions, for example, uh, because Cindy mentioned it earlier, right? >>You can store known locations of an individual in an operational database, uh, with Cloudera that would be HBase. And as an individual makes a new transaction, their geolocation that's in that transaction data can be enriched with previously known locations of that very same individual. And all of that enriched data can be later used downstream for predictive analysis, predictable. So the data has been enrich. Uh, now it needs to be transformed. We want the data that's coming in, uh, you know, Avro and Jason and binary and whatever other format to be transformed into a single common format. So it can be used downstream for stream processing. Uh, again, this is going to be done through clutter and data flow, which is backed by NIFA, right? So the transformed semantic data is then going to be stricted to Kafka and coffin. It's going to serve as that central repository of syndicated services or a buffer zone, right? >>So coffee is going to pretty much provide you with, uh, extremely fast resilient and fault tolerance storage. And it's also gonna give you the consumer APIs that you need that are going to enable a wide variety of applications to leverage that enriched and transformed data within your buffer zone, uh, allowed that, you know, 17. So you can store that data in a distributed file system, give you that historical context that you're going to need later on for machine learning, right? So the next step in the architecture is to leverage a cluttered SQL stream builder, which enables us to write, uh, streaming SQL jobs on top of Apache Flink. So we can, uh, filter, analyze and, uh, understand the data that's in the Kafka buffer in real time. Uh I'll you know, I'll also add like, you know, if you have time series data, or if you need a lab type of cubing, you can leverage kudu, uh, while EDA or, you know, exploratory data analysis and visualization, uh, can all be enabled through clever visualization technology. >>All right, so we've filtered, we've analyzed and we've explored our incoming data. We can now proceed to train our machine learning models, uh, which will detect anomalous behavior in our historically collected data set, uh, to do this, we can use a combination of supervised unsupervised, uh, even deep learning techniques with neural networks. And these models can be tested on new incoming streaming data. And once we've gone ahead and obtain the accuracy of the performance, the scores that we want, we can then take these models and deploy them into production. And once the models are productionalized or operationalized, they can be leveraged within our streaming pipeline. So as new data is ingested in real-time knife, I can query these models to detect if the activity is anomalous or fraudulent. And if it is, they can alert downstream users and systems, right? So this in essence is how fraudulent activity detection works. >>Uh, and this entire pipeline is powered by clutters technology, right? And so, uh, the IRS is one of, uh, clutter's customers. That's leveraging our platform today and implementing, uh, a very similar architecture, uh, to detect fraud, waste, and abuse across a very large set of historical facts, data. Um, and one of the neat things with the IRS is that they've actually recently leveraged the partnership between Cloudera and Nvidia to accelerate their spark based analytics and their machine learning, uh, and the results have been nothing short of amazing, right? And in fact, we have a quote here from Joe and salty who's, uh, you know, the technical branch chief for the research analytics and statistics division group within the IRS with zero changes to our fraud detection workflow, we're able to obtain eight times to performance simply by adding GPS to our mainstream big data servers. This improvement translates to half the cost of ownership for the same workloads, right? So embedding GPU's into the reference architecture I covered earlier has enabled the IRS to improve their time to insights by as much as eight X while simultaneously reducing their underlying infrastructure costs by half, uh, Cindy back to you >>Chef. Thank you. Um, and I hope that you found, uh, some of the, the analysis, the information that Sheva and I have provided, um, to give you some insights on how cloud era is actually helping, uh, with the fraud waste and abuse challenges within the, uh, the public sector, um, specifically looking at any and all types of data, how the clutter platform is bringing together and analyzing information, whether it be you're structured you're semi-structured to unstructured data, both in a fast or in a real-time perspective, looking at anomalies, being able to do some of those on detection, uh, looking at neural network analysis, time series information. So next steps we'd love to have additional conversation with you. You can also find on some additional information around, I have caught areas working in the, the federal government by going to cloudera.com solutions slash public sector. And we welcome scheduling a meeting with you again, thank you for joining us Sheva and I today. We greatly appreciate your time and look forward to future progress. >>Good day, everyone. Thank you for joining me. I'm Sydney. Mike joined by Rick Taylor of Cloudera. Uh, we're here to talk about predictive maintenance for the public sector and how to increase assets, service, reliability on today's agenda. We'll talk specifically around how to optimize your equipment maintenance, how to reduce costs, asset failure with data and analytics. We'll go into a little more depth on, um, what type of data, the analytical methods that we're typically seeing used, um, the associated, uh, Brooke, we'll go over a case study as well as a reference architecture. So by basic definition, uh, predictive maintenance is about determining when an asset should be maintained and what specific maintenance activities need to be performed either based upon an assets of actual condition or state. It's also about predicting and preventing failures and performing maintenance on your time on your schedule to avoid costly unplanned downtime. >>McKinsey has looked at analyzing predictive maintenance costs across multiple industries and has identified that there's the opportunity to reduce overall predictive maintenance costs by roughly 50% with different types of analytical methods. So let's look at those three types of models. First, we've got our traditional type of method for maintenance, and that's really about our corrective maintenance, and that's when we're performing maintenance on an asset, um, after the equipment fails. But the challenges with that is we end up with unplanned. We end up with disruptions in our schedules, um, as well as reduced quality, um, around the performance of the asset. And then we started looking at preventive maintenance and preventative maintenance is really when we're performing maintenance on a set schedule. Um, the challenges with that is we're typically doing it regardless of the actual condition of the asset, um, which has resulted in unnecessary downtime and expense. Um, and specifically we're really now focused on pre uh, condition-based maintenance, which is looking at leveraging predictive maintenance techniques based upon actual conditions and real time events and processes. Um, within that we've seen organizations, um, and again, source from McKenzie have a 50% reduction in downtime, as well as an overall 40% reduction in maintenance costs. Again, this is really looking at things across multiple industries, but let's look at it in the context of the public sector and based upon some activity by the department of energy, um, several years ago, >>Um, they've really >>Looked at what does predictive maintenance mean to the public sector? What is the benefit, uh, looking at increasing return on investment of assets, reducing, uh, you know, reduction in downtime, um, as well as overall maintenance costs. So corrective or reactive based maintenance is really about performing once there's been a failure. Um, and then the movement towards, uh, preventative, which is based upon a set schedule or looking at predictive where we're monitoring real-time conditions. Um, and most importantly is now actually leveraging IOT and data and analytics to further reduce those overall downtimes. And there's a research report by the, uh, department of energy that goes into more specifics, um, on the opportunity within the public sector. So, Rick, let's talk a little bit about what are some of the challenges, uh, regarding data, uh, regarding predictive maintenance. >>Some of the challenges include having data silos, historically our government organizations and organizations in the commercial space as well, have multiple data silos. They've spun up over time. There are multiple business units and note, there's no single view of assets. And oftentimes there's redundant information stored in, in these silos of information. Uh, couple that with huge increases in data volume data growing exponentially, along with new types of data that we can ingest there's social media, there's semi and unstructured data sources and the real time data that we can now collect from the internet of things. And so the challenge is to collect all these assets together and begin to extract intelligence from them and insights and, and that in turn then fuels, uh, machine learning and, um, and, and what we call artificial intelligence, which enables predictive maintenance. Next slide. So >>Let's look specifically at, you know, the, the types of use cases and I'm going to Rick and I are going to focus on those use cases, where do we see predictive maintenance coming into the procurement facility, supply chain, operations and logistics. Um, we've got various level of maturity. So, you know, we're talking about predictive maintenance. We're also talking about, uh, using, uh, information, whether it be on a, um, a connected asset or a vehicle doing monitoring, uh, to also leveraging predictive maintenance on how do we bring about, uh, looking at data from connected warehouses facilities and buildings all bring on an opportunity to both increase the quality and effectiveness of the missions within the agencies to also looking at re uh, looking at cost efficiency, as well as looking at risk and safety and the types of data, um, you know, that Rick mentioned around, you know, the new types of information, some of those data elements that we typically have seen is looking at failure history. >>So when has that an asset or a machine or a component within a machine failed in the past? Uh, we've also looking at bringing together a maintenance history, looking at a specific machine. Are we getting error codes off of a machine or assets, uh, looking at when we've replaced certain components to looking at, um, how are we actually leveraging the assets? What were the operating conditions, uh, um, pulling off data from a sensor on that asset? Um, also looking at the, um, the features of an asset, whether it's, you know, engine size it's make and model, um, where's the asset located on to also looking at who's operated the asset, uh, you know, whether it be their certifications, what's their experience, um, how are they leveraging the assets and then also bringing in together, um, some of the, the pattern analysis that we've seen. So what are the operating limits? Um, are we getting service reliability? Are we getting a product recall information from the actual manufacturer? So, Rick, I know the data landscape has really changed. Let's, let's go over looking at some of those components. Sure. >>So this slide depicts sort of the, some of the inputs that inform a predictive maintenance program. So, as we've talked a little bit about the silos of information, the ERP system of record, perhaps the spares and the service history. So we want, what we want to do is combine that information with sensor data, whether it's a facility and equipment sensors, um, uh, or temperature and humidity, for example, all this stuff is then combined together, uh, and then use to develop machine learning models that better inform, uh, predictive maintenance, because we'll do need to keep, uh, to take into account the environmental factors that may cause additional wear and tear on the asset that we're monitoring. So here's some examples of private sector, uh, maintenance use cases that also have broad applicability across the government. For example, one of the busiest airports in Europe is running cloud era on Azure to capture secure and correlate sensor data collected from equipment within the airport, the people moving equipment more specifically, the escalators, the elevators, and the baggage carousels. >>The objective here is to prevent breakdowns and improve airport efficiency and passenger safety. Another example is a container shipping port. In this case, we use IOT data and machine learning, help customers recognize how their cargo handling equipment is performing in different weather conditions to understand how usage relates to failure rates and to detect anomalies and transport systems. These all improve for another example is Navistar Navistar, leading manufacturer of commercial trucks, buses, and military vehicles. Typically vehicle maintenance, as Cindy mentioned, is based on miles traveled or based on a schedule or a time since the last service. But these are only two of the thousands of data points that can signal the need for maintenance. And as it turns out, unscheduled maintenance and vehicle breakdowns account for a large share of the total cost for vehicle owner. So to help fleet owners move from a reactive approach to a more predictive model, Navistar built an IOT enabled remote diagnostics platform called on command. >>The platform brings in over 70 sensor data feeds for more than 375,000 connected vehicles. These include engine performance, trucks, speed, acceleration, cooling temperature, and break where this data is then correlated with other Navistar and third-party data sources, including weather geo location, vehicle usage, traffic warranty, and parts inventory information. So the platform then uses machine learning and advanced analytics to automatically detect problems early and predict maintenance requirements. So how does the fleet operator use this information? They can monitor truck health and performance from smartphones or tablets and prioritize needed repairs. Also, they can identify that the nearest service location that has the relevant parts, the train technicians and the available service space. So sort of wrapping up the, the benefits Navistar's helped fleet owners reduce maintenance by more than 30%. The same platform is also used to help school buses run safely. And on time, for example, one school district with 110 buses that travel over a million miles annually reduce the number of PTOs needed year over year, thanks to predictive insights delivered by this platform. >>So I'd like to take a moment and walk through the data. Life cycle is depicted in this diagram. So data ingest from the edge may include feeds from the factory floor or things like connected vehicles, whether they're trucks, aircraft, heavy equipment, cargo vessels, et cetera. Next, the data lands on a secure and governed data platform. Whereas combined with data from existing systems of record to provide additional insights, and this platform supports multiple analytic functions working together on the same data while maintaining strict security governance and control measures once processed the data is used to train machine learning models, which are then deployed into production, monitored, and retrained as needed to maintain accuracy. The process data is also typically placed in a data warehouse and use to support business intelligence, analytics, and dashboards. And in fact, this data lifecycle is representative of one of our government customers doing condition-based maintenance across a variety of aircraft. >>And the benefits they've discovered include less unscheduled maintenance and a reduction in mean man hours to repair increased maintenance efficiencies, improved aircraft availability, and the ability to avoid cascading component failures, which typically cost more in repair cost and downtime. Also, they're able to better forecast the requirements for replacement parts and consumables and last, and certainly very importantly, this leads to enhanced safety. This chart overlays the secure open source Cloudera platform used in support of the data life cycle. We've been discussing Cloudera data flow, the data ingest data movement and real time streaming data query capabilities. So data flow gives us the capability to bring data in from the asset of interest from the internet of things. While the data platform provides a secure governed data lake and visibility across the full machine learning life cycle eliminates silos and streamlines workflows across teams. The platform includes an integrated suite of secure analytic applications. And two that we're specifically calling out here are Cloudera machine learning, which supports the collaborative data science and machine learning environment, which facilitates machine learning and AI and the cloud era data warehouse, which supports the analytics and business intelligence, including those dashboards for leadership Cindy, over to you, Rick, >>Thank you. And I hope that, uh, Rick and I provided you some insights on how predictive maintenance condition-based maintenance is being used and can be used within your respective agency, bringing together, um, data sources that maybe you're having challenges with today. Uh, bringing that, uh, more real-time information in from a streaming perspective, blending that industrial IOT, as well as historical information together to help actually, uh, optimize maintenance and reduce costs within the, uh, each of your agencies, uh, to learn a little bit more about Cloudera, um, and our, what we're doing from a predictive maintenance please, uh, business@cloudera.com solutions slash public sector. And we look forward to scheduling a meeting with you, and on that, we appreciate your time today and thank you very much.

(upbeat music) >> Hello, and welcome to today's session of the AWS Global Public Sector Partner Awards. I'm delighted to introduce our next guests to highlight the award for Best Partner Transformation, Best Telco Solution, and of course, I'm your host Natalie Erlich for theCUBE. We are now joined by Avishai Sharlin Division President at Amdocs Technology, and Ralf Hellenbran, Program Director of Technology at Vodafone Germany. Thank you, gentlemen, for joining the program. >> Thank you for having us. >> Our pleasure. >> Let's have the opening question for both of you. You know, but let's first start with Avishai. What has been the highlight to date in the journey of both Amdocs and Vodafone? >> Well, it's a good question. I believe that the highlight was the teaming and getting things done together as partners. Unlike many previous experiences, this time, we understood that success equals us working hand in hand together, making sure that we overcome and achieve everything as true partners. So the greatest obstacles and also the biggest achievement were done together as one team. We always speak about the hurdles, we negotiate sometimes. But eventually, we're coming to the solution together, and making sure that everything is properly managed and properly done in the right timing, and according to plans. >> Terrific, well, Ralf, let's go to you. What do you see as the highlights of this collaboration. >> Now exactly what Avishai said, but let me add to that. What we are following is a real collaborative approach. Now, there's a lot of strengths in that approach. Because we are using for example, swarm intelligence, we are using elements, which you see in clouds attempts as well, for example, yeah, but you see it in agile attempts and agile working methods. And this is what we applied. And as Avishai said, we are doing that as real partners in the program. And we are pulling a lot of strengths out of that by detecting problems early, we have a high level of transparency, we put everything on the table, and differences that we do not fight about the problems. We work collaborative on the solution. And that's really kind of new to the industry we are working in. And that's kind of game changing for it. At the beginning, we said it will be game changing if it works. Now we see that it does. >> Terrific. Well, why do you think generally speaking, that the Telco industry has been so slow, to you know, embrace these kinds of innovations? Let's start with Avishai. >> Yeah. It's less about I think the actual technology, it's more about a handful of parameters that need to be aligned, once you are trying to address these big transformations. You need to upskill a lot of people, you need to educate your manpower, to new technologies and new ways and processes, how to embrace DevOps, how to work in a cloud environment, how to embrace an agile, safe methodology. So there are many small pockets of things that needs to be changed. Not a single element, actually is the same as like five years ago. So in a way, if the organization as a whole, is not being transformed, it's very tough to embrace all those new technologies and succeed in such a journey. So for us, and I think also to our partners in Vodafone, it was a mutual understanding that we need to not just work together, but also tackle the new technologies and methods and processes all together and change the entire organization and ecosystem in order to succeed. In many other cases in the industry, we see that some pockets are not being changed. And then even if the technology is right, you're missing the upscaling of people, if you upskill the people and you forgot the technology, and so on so forth. >> Perfect now, Ralf, I'd love for you to respond to that question as well. >> So the Telco industry is a quite complex industry, that you look to the product it seems to be quite easy. You pick up a phone and you do a phone call or you go to the internet and so on and so forth. But if you think of all the services, which you're using via your smartphone, for example, yeah, it's far away from just doing a phone call. So at the same time where the Telco industry is producing and selling products, it's producing and selling services. At the same time, while you're using it for leisure, you're also using it for emergency calls. So there's a high level of safety, which we need to bring, and we need to pair it with a lot of innovation elements, right, both together. Now, if you take all this and you think of the complexity, it's not easy to introduce new methods and new ways of working, etc, to such an industry, again you need to take two things into account, you need to make it very safe and stable and educated and controlled. And at the same time, you need to be very fast, because it's a fast moving industry. And both together explains how we adopt it and why sometimes we are a bit slower than others, because the trial and error, yeah, it's not that easy, because the error cannot be allowed in big scale. The more I'm happy that in the approach we're taking together with Amdocs and also AWS, we can apply these new methods while keeping the safety and stability. >> Terrific, well, thank you for outlining that safety methodology. Avishai, I'd like to move this back to you. How are you redefining this operation through DevOps and automation? >> Oh, that's an interesting question. I think that automation, needs to be baked into almost everything that we're doing in such a transformation. It's not from the basic technology stuff, but it goes into all the processes, the way you develop, the way you test. The way you deploy, the way later on, you're making sure that everything run in the right way. So automation is key fundamental element in the end to end journey of such a big transformation, especially if you're going into agile development, and you need to fail fast, react fast, change fast, and then continue onwards with a new solution. So first, as you rightfully said, it's automation. And DevOps is also key over here, because you need to make sure that what you develop is also something that you deploy in the right way. So you need to put in place all the right mechanism, such as (indistinct), and the cloud frameworks, and the relevant different technologies that are adhering into this end to end solution. >> Perfect, now, Ralf, what are your thoughts? How are you redefining the operation now through DevOps and automation? >> We are trying to solve the paradox. Again, the paradox is we want to have things very stable, that would dictate us to do very detailed plans and to adhere to it and so on this is what we did in the past, it fostered for example, taylorism, and similar things. Now, we want to go a step further, we want to apply agile methods, we want to dismantle the taylorism. And the techniques around DevOps, cloud operation, etc, agile methods help us to do that. Now, while we are transforming our way of working, we don't want to lose the good elements of what we have been doing before, we want to do a step forward and not at the same time step back. And therefore we are combining things. And automation, for example, is one way to do that. DevOps is another way to do that. We are joining the good thinking of operations and the good thinking of development together, and we are pulling additional strengths out of that, while not taking into account or taking on board the weaknesses of the former approach. So it's a stepwise transformation we are following. Automation helps us to focus on the real problems, and not on the things you can automate by technology. >> Terrific. Well, now Avishai, bringing this back to you, Ralf talks about agility and also DevOps, explain the journey today on such a large program. >> The the journey, in what sense? Can you give me some coloring? >> Yeah tell us about this collaboration and keeping that in mind, keeping in mind agility as well as DevOps. You know, the step by step process in developing such a large collaborative program. >> Thank you for clarification. So I think that the journey as a whole had several components, (indistinct) and myself also the beginning about the nature of being true partners here. But it is also about establishing something very new in the industry. Many of the things that we're working are, you know, the first time that we're doing agile manner of developing software and testing, it's so fast, it's the first time we're implementing the latest and greatest DevOps technologies. The first time, we're adhering into new standards and way and behavior from a modernized technology organization. So in a way, this journey is all about a mixture of innovation, new stuff, on one hand, aligned with a very, very tight in a good way, I would call it German engineering, in the sense of making sure the things are in place and making sure that the processes are well defined. And we're seeing at any given point, the different status we're in, what needs to be improved, what is going well, and what future lies ahead. >> Staying with that topic on the journey opening to both of you, and perhaps Ralf would like to jump in here, first, how have AWS technologies been featured as part of this journey. >> AWS has been chosen wisely by us because of its technology components brought to the table. Now, without now pointing to a particular service, which we are using, we talked about automation, we talked about DevOps, now everyone can itself about how AWS in general helps to foster that, the sheer fact that we can merge the different way of working with a different mindset of people working in our collaboration and technology components coming not only, but also from AWS, this is ensuring our success. If you would pull out one of these elements, yeah, out of the equation, that most probably it would not work. I have problems to rate which element is more important, they are all part of the puzzle and otherwise, you will not see the picture and create the picture. So in a nutshell, we are utilizing the AWS technologies in order to allow the speed of development, lots of first times which we have in our collaboration, and the AWS technologies are an essential part of that. >> Terrific and Avishai, what are your thoughts on that? >> I think that the collaboration with AWS goes in several, in a way different shapes and form. On the technology, pure technology level, we're utilizing native EKS, we're moving with the managed Kubernetes. We're using, you know the latest technology in databases, and many other very, very cool technologies coming from AWS. And on a different level, completely different level, I think that AWS understands the behavior of complex enterprise and are assisting us with programs, looking into well architected framework and how to work in a managed environment and what are the technologies that we need to utilize. And also in, from an Amdocs perspective, something that assisted us a lot in this journey, we have a unique technology which defines an end to end solution to development within a micro service cloud native environment, we'll call it M360. AWS assisted a lot in making this a mature technology and allowing us to develop faster and fully utilize the benefits of cloud native environments. >> Terrific, now to both of you, what do you see as the next step in your collaboration together? Let's bring this to Ralf. >> There is no distinct next step. And maybe this is the consequence of the way of working we have established. There are many small steps we will pursue and most probably, if you want to know, which are the next steps, you need to talk to our teams. This is another aspect of this new way of working, which we apply. The people working in that approach, they tell us how they construct, how they structure this approach. If I would summarize it, we are constantly tearing down the walls between the companies, between silos, between departments working in that collaboration, and we are getting more close together every day. And solving problems quicker, we are getting them quicker on the table, we are getting them quicker, and softer, faster, soft, and AWS, Amdocs are part of this. And this is really nice to see and be part of, that this is really happening. So the next step is, foster the collaboration. >> Avishai do you have any thoughts? >> Yeah, on a personal level, I think the next step would be to glide together in Europe. But on a more serious note, I think that this is becoming like a true partnership. And I think that I see a lot of empowerment coming from both sides, allowing the team to develop together, to think together and to start to create new stuff, that even if you plan ahead, you will never achieve without true collaboration. So this empowerment, the fact that the teams feel that they can do things on their own, and make one and one equals three, two, or you know, or seven, is the big change that I see in front of us. And I really feel it in the air. And I also feel it in in the way we act and we move forward. >> Yeah, so Ralf, how do you see that this program will enable continuous innovation? >> Oh, it does already. So if you're looking to big transformation programs of the past, (indistinct) beside the fact that lots of them actually did not achieve what they are, what they were asked to achieve. Usually big programs, do big plans, and then you have a very long period of preparation. And then usually you have a rather big bank or life and then everything shall be fun. That sometimes work but not most times, it's difficult. Now within our program, we are doing that in collaboration, but step by step by step. And it's more an evolution than a revolution, which we are doing. At least in the way we deploy things, again, we are back to DevOps, continuous integration, continuous deployment and so on all these elements, which you can see in these approaches. And this is where the wheel spinning slice. So it's evolving step by step. And it's bringing benefits step by steps. So the benefits are already in place into to a certain extent, and they're constantly growing. >> Terrific, Avishai, what are your thoughts? How do you see the innovation of being able to continue and even further? >> In a way we're in a world that everything is in continuum, so it's continuous delivery, and continuous development and also continuous innovation. As long as you know, the ecosystem of ours continues to innovate as a whole, we are part of it. And inevitably, we are part of the larger ecosystem on one hand, and also players within it on a smaller scale in this project and as organization. So I think innovation is baked into everything we're doing today. Sometime it's small incremental steps, sometimes it's big, innovative moves, but all in all, it's something that is currently part of our DNA. >> And how is this system helping you both you know, be more proactive? Either one of you who would like to go first? >> No, I started first. >> Avishai? Okay. So, we are data driven, we are way more data driven. And by knowing exactly what is happening, we can be faster, we can be more innovative, we can be more productive. So, in cases where we either discover a problem or we discovering opportunity, we are much faster in analyzing whether it's really one, how should we redirect on that? How can we solve it or utilize it? And that's really working well. >> Perfect. And, you know, Avishai, feel free to join in on that too. >> In the digitized economy, I think that productivity comes a lot from the business side. If there is something that completely changed lately is the fact that business people are driving many, many changes on one end, and technology is here to adhere on one end and flexible to to move forward. So many of the productive concepts are coming from non technology savvy people, and the ability of what we're doing together to adjust and support different business behaviors and business models, and also, you know, business initiatives is thought of as being productive and being able to adapt into the digitalized economy. >> Let me join in on that one, what Avishai said, Let's think of a business person who wants to change something, and you don't know whether it's a white way as a corporation. Now you bring in the technology bits and pieces from different angles, and all of a sudden, you can combine it with a data driven approach, then, you know much better how to react on this business demand and how to bring it to life by using technology. Yeah, that might be a very high level of example of what we're doing here. Again, collaboration, get it done together with is the theme of that, technology is a very important part of that, paired with the business. >> Yeah, we talked on some very broad terms like themes, collaboration, innovation, I just want to focus a bit now on automation. Why do you think it is so critical to the vision of this program, Avishai. >> First of all, because it ends with ation, and everything that has this, but what I think that we started with this, automation is fundamental to everything that needs to be nimble, everything that needs to be fast. You cannot do it manually. And if you want to react either to a business demand or to a data driven decision, analytic decision, if you want to adopt new technology, if you want to test a new business scenario or technology scenario, you need automation to be part, inevitable part of everything that you're doing. So automation is a key element in everything that we're doing. And it's critical part of also the way to look into the future and to make sure that everything is working the right way. >> Perfect Ralf, any quick thoughts on that? >> Actually, nothing, nothing to add. >> All right, terrific. Well, it's been so wonderful to have you on the program. I know people are coming in from all over the world to join us. Really fantastic opportunity to highlight this important innovation in the Telco sector. Glad to have you here. Ralf Hellenbran, Program Director of Technology at Vodafone Germany, as well as Avishai Sharlin, the Division President at Amdocs Technology. we're highlighting the award that they won as part of the AWS, Global Public Sector Partner Awards. So great to have you on the show. And I'm your host Natalie Erlich, do stay tuned for more coverage. (upbeat music)

(upbeat music) >> Hello, and welcome to today's session of the 2021 AWS Global Public Sector Partner Awards. I'm delighted to present our special guests for today's program and they are Kyle Hines, VP Strategic Accounts at Presidio as well as chief Chuck Hoskin, Jr., chief of the Cherokee Nation. Welcome to the program, gentlemen >> Thank you. >> Terrific, well, delighted to have you here, we're going to discuss the key award of best partner transformation, most impactful nonprofit partner, of course now highlighting some of the technologies now being technology now being leveraged to help preserve the Cherokee language as well as its culture. Now, Chuck, I'd like to start with you and if you could describe some of the challenges that the Cherokee nation is now faced with in terms of preserving the language and its culture and how you see technology being able to really help preserve it. >> Well, thank you, Natalie. It was really good to be with you all today. The Cherokee language and culture is what makes us unique as a people. It's the link that links us back to time and immemorial through generations. And over those generations, there've been many threats to our language and culture. There's been disease after European contact, there's been dispossession, there's been our forced removal on the trail of tears. Other pressures in more modern times have continued to erode our language and culture, including, boarding schools, the public school system through most of the 20th century as Cherokee Nation has gotten back on its feet, that is to say when the govern the United States has allowed Cherokee Nation to do what we've always done well which is to govern ourselves, chart our own destiny, and preserve our life ways, we've been able to make preservation efforts but those generations of eroding our language and culture had coming to steep costs. We're the largest tribe in the country, 392,000 citizens and by the way we're mostly in Northeast, Oklahoma but we have Cherokees living all over the country even all over the world. And we only have 2000 fluent speakers left. So it's a great challenge to save a language that's truly endangered. And if we don't save it generations from now we may do a number of things exceedingly well as we do today, business, providing education and housing, creating a great healthcare system, but we will have lost that thing that makes us a unique people, that thing that links us back to our past. And so what we're doing today, working with great partners like Presidio is just indispensable to what's really our most important mission. >> Yeah, terrific. Well, thank you so much for those insights. I'd like to switch it over to Kyle and hear about the technologies now being utilized to preserve the Cherokee language and culture. >> Sure, happy to Natalie and thanks for having us this morning. So yeah, when we started to work with the Cherokee Nation, it was very clear to us that, there's obviously a higher power or a higher mission here. And so it's really been an honor to work with the chief and the nation and what we've been able to do is is take what the Cherokee Nation is trying to do in terms of language and cultural preservation and build solutions in really a very modern way. So between Inage’i, the 3D mobile open-world game and the virtual classroom platform, it's entirely a cloud native serverless solution in AWS, using a lot of the most modern tools and technologies in the marketplace. For example, in the mobile game, it's built around unity and the virtual classroom platform is built around the Amazon chime SDK, which allows us to really build something that is very clean and light and focused on what the nation is trying to achieve and really cut out a lot of the baggage and the other sort of plumbing and various other technologies that this would have, this type of solution would have taken just a few short years ago. >> Yeah, terrific. Well, Kyle, staying with you, what do you think were some of the factors behind the development of this solution? >> Yeah, so I think flexibility was key. Was maybe the biggest design goal in building these solutions because you learn a lot when you originally set out to build something and it starts to impact real users, and in this case, speakers of the Cherokee Nation, you learn a tremendous amount about the language and how it's used and how people communicate with each other. And so the main design goal of the solutions was to allow a sort of flexibility that lets us adapt. And every time we learn something and every time we find something that works or perhaps doesn't work quite as well as was imagined, we have the flexibility to change that and kind of stay nimble and on our toes. >> Terrific, well, Chuck, now switching over to you, why do you think that some of these, platforms like the virtual classroom are so effective with Cherokee speakers? >> Well, a couple of reasons, one pandemic related, during COVID the worst public health crisis the world seen in living memory, we have had to adapt quickly to continue on our mission to save this language. We couldn't afford a year off in terms of pairing speakers, by the way, most of our fluent speakers are over the age of 70, with young people who need to learn the language and be the new generation of speakers. So it's been really important that during those difficult times we could connect virtually and the technology we've been using has worked so effectively, but the other is really irrespective of what's going on in terms of having to isolate, and social distance and things of that nature during COVID, and that is just making sure we can make this language accessible, particularly to young people in a manner in which they are becoming accustomed to learning things throughout the rest of the world. And so using platforms that they're familiar with is very important but it also has to be something that an older generation of these fluent speakers, as I say most of them are over 70, can use. And that's what really has been so effective about this platform. It's so usable. Once you introduce it to people whether it's a young person who can adapt pretty quickly 'cause they're growing up immersed in it, or it's someone who has not been familiar with that technology, with just a little bit of showing them how to use it, suddenly this classroom becomes just like you're in person. And that makes all the difference in the world in terms of connecting these young people with their elders. As the other thing is Cherokees are by nature very much part of a big extended family. And so that personal connection that you can maintain through this platform is really important. I think it's going to be the key to how we save this language, because as I say we have Cherokees all over the country, even all over the world and we're going to harness our numbers, the large population we have and find those with the interest and aptitude to learn the language, we must use this technology and so far it's worked well. >> Yeah, terrific, and now switching over to Kyle, we'd love to hear from you how your team developed this technology. How they really thought out, what kinds of methods are really going to drive the interaction and the immersion and engagement among these disparate demographics of, elderly Cherokees and also the young generation. So, how did your team go about developing that? >> Yeah, it's a very good question because in a situation like this, there is no shortage of different ways that you could have built a solution like this. There are a lot of different ways that it could have been done. So the tax that we took was a rigorous focus on the user experience and on the experience of the speaker. And that allowed us to detach ourselves to a large degree from what were the exact technology choices that were implemented in terms of AWS services, other open source packages that run on AWS, it's being able to focus completely on what the nation was trying to achieve with their speakers, both through the game and the virtual classroom platform. It let us take a lot of other design decisions and technology choices sort of into the background and behind a level of abstraction. And so there's always quite a bit of rigorous testing and really making sure you understand how something's going to perform in the wild, but the reality of the situation was, the whole reason for doing it was the experience of the speakers, both in the game and in the classroom platform. So we stayed very focused on that and made technology decisions sort of second fiddle or lower priority. >> Terrific, well, Chuck, how do you think that these kinds of innovations could be applied to other areas of the Cherokee school system? >> Well, our greatest challenge is preserving language and culture, but we also have as part of our mission to educate this new generation of Cherokees coming up. For years and years, really generations, Cherokees who were able to get a good education many of them left our tribal lands for new opportunities. And so we lost a great deal because of the economic pressures here in Northeast, Oklahoma, particularly on our Cherokee lands. So the task now is to generate opportunity for a new generation coming up. Education is key to that and so if we want to create a pipeline of young Cherokees who want to get into the healthcare fields, want to get into aerospace, want to get into other professions, we've got to create an education system that is steadier and modern. We have a school that is K through 12th grade, K through the senior year, and so we have an opportunity really to do that. And I think for the first time in our history, in this era, I'm talking elect the last few decades, we are able to really craft education in a way that works for us and using technology and making choices about what that technology is, is important to us. It's a bygone era in which the federal government or the state is sort of imposing on us what choices we make. Now we can reach out with great partners all over the world like Presidio and say what solution can work for our classroom? When we can identify what the great demands are on the reservation in terms of jobs. And one of the great demands we have is healthcare. So how can we use technology to inspire little Cherokee boys and girls to grow up and be doctors and nurses here in just a few decades when we're building this great health system? Well, we're going to use technology to do it. So the possibilities are really unlimited and they need to be because we think our potential here in Cherokee Nation is unlimited. >> Yeah, I mean that's terrific to hear how technology is really encouraging younger generations to study, learn and really push themselves further. Kyle, I'd like to switch over to you and hear a little bit about the benefits of launching this kind of platform on AWS. >> Yeah, there are a lot of benefits to building this on AWS. And I think that it spans a couple of categories, even. I mean, from a technological perspective there was every tool and every service that we needed to build both of the solutions that we built right there in AWS. And when there was a, when there was a time where we needed to jump out and use a project outside of AWS, running on AWS such as the unity engine, AWS makes that very easy. So I would say that the choice was easy because there are technological realities and the breadth and the depth of the technological portfolio in AWS combined with the partnership that we get from them, It's really, you know, there's a lot of support when it comes to, Hey we're working with the Cherokee nation on something that's extremely important. We need your help. We need you to help us figure this out. It's never been hard to get that partnership. >> Terrific, and also following up on that, love to hear how AWS really helped with flexibility and also the cost effective effectiveness of this kind of platform. >> Yeah I would take those questions backwards or in reverse order because the cost-effectiveness of the solution is really, it's really something to make note of because when we build something in the way that we built these platforms they're serverless and event driven. Meaning that the Cherokee Nation is not paying for a solution constantly as we would in lives past running things in data centers and such. It really, the services in AWS allow us to say, Hey, let's spin up certain pieces of functionality when they're needed as they're being used. And the meter is running during that time, and the cost is occurred during the time it's being used and not all of the time. So that really has a dramatic impact on cost effectiveness. And then from a flexibility standpoint, as we learn new things, as we evolve the platform as we grow this out to more and more speakers and to more and more impact to the Cherokee Nation, we have all kinds of different technology choices that we can make and it's all contained within AWS. >> Yeah, and I'd like to open this now to both of you, starting with Chuck, how do you think this kind of technology could be applied to other cultures or languages that re seeking to preserve themselves? There's so many languages in the world that are now dying out because most of us are only speaking, just a few like English, Spanish, just a few others, what steps can be taken so that humanity can preserve these important languages? >> Well, you're right. There are so many endangered languages around the world and indigenous languages are unfortunately dying all over the world all the time, even as we speak, they're slipping away. The United nations is dedicated the next decade to the preservation of indigenous languages. That's gotten many leaders around the world thinking about how we can save languages here in this era. And I would encourage any tribal leader in particular in the United States, but I think it certainly applies around the world to seek out this technology. I mean, Cherokee Nation's in a position now where we can seek out the best in the world in terms of partnerships. And we've found that in Presidio. And of course they're using AWS which means they're using the best in the world and so the technology exists, and the willingness to work together exist. And I think generations ago that would have been not something we could have connected well on in terms of partnering with companies that were doing cutting edge things. So if you're looking to connect generations in terms of learning and sharing the language, which is just I cannot stress enough how indispensable that is to language preservation, this type of technology will do it. There are some, I think that may think, and I don't have a technology background, that if you're using this cutting edge technology, I mean this is the best in the world that you're going to speak only to this young generation coming up, and maybe it's inaccessible to an older generation. It's just not the case. This is so user-friendly that we we've been able to connect elders with young people. And if anyone in the world interested in preserving languages could see this in action, could see a young person sitting next to an elder talking about the technology or connecting virtually, it would change their whole perspective on what technology means for language reservations because I promise you all over the world the great challenges you have this group of older generations of people who know the language. They have it in their hearts, they have it in their minds and they're slipping away just from the passage of time. Connecting them with the generation coming up is just what we need to do. This technology allows us to do it. >> Yeah, Chuck following up on that when I hear about elderly people being able to connect with the younger generations in this way and share their history and their culture I'm sure that also, It must have a positive mental effect for them. Right, so elderly are often isolated. Do you have any insight on that? Any quality of insight what you've heard from people using this? >> Yeah, absolutely. And I think the last year has proven how valuable it is. I mean, we lost over 50 fluent Cherokee speakers and I mentioned earlier in the program, that we only have 2000 left. 50 to COVID and more to just the passage of time and old age. But we have many that are active and engaged in language preservation and they have said to me how valuable it's been to be able to be at home and yet still feel like they're part of this great mission that we have at the Cherokee Nation. Understand that this mission that we have is on par with what any nation in history has set as a goal to shoot for whether it's the United States wanting to land a man on the moon, we're trying to save the language. This is that level of importance. And so for an elder to feel like they're connected and still contributing during this past year difficult times, that makes all the difference in the world. And even as I say, as the pandemic recedes and we hope it continues to recede, there is still a need for elders to stay connected. And in many cases they cannot due to poor health, due to the lack of transportation, this knocks down those barriers and so there's a great deal of joy that has been gained from using this technology. And honestly, just talking to elders about young people getting the opportunity to play this video game even some elders that were voice actors in this game, that Presidio helped us develop. I mean, I can't tell you how important that is for somebody to use their language, to make a living. And that's part of how you preserve a language. Presidio has showed us a way that we can do just that. So we're not only training new speakers, we're giving this opportunity many cases to elders to do something that is very productive with the wonderful gift they have, which is the Cherokee language. >> Terrific, well that is really inspiring because potentially this technology could be utilized by generations to come. The current young people that are using this will one day be the elderly. So, Kyle, how do you see this technology potentially on this platform being evolved? What's the next step to keep it really up to date for future generations as it's evolving. >> Yeah, there's a lot of plans on where to take this I can tell you, honestly. From the perspective of the mobile game, you're building on a platform of an open world game means that the imagination is the limit quite honestly. So there are a lot of new characters and new levels and new adventures that are plans to further immerse the speakers in the platform. And I think that will, that will help with reach and it will help with the amount of connection that's built to the chief's point about bridging the older generations into the younger generations over that common bond of the language and the culture that keeps those connections alive. And so we want to expand the mobile game Engage, the navigate to be as accessible and as wide reaching and immersive as it possibly can, and there are a lot of plans in the works for that. And then with the virtual classroom platform, we started with a various focused constituency within the nation of the language immersion school. And there are many other educational services and even healthcare to the chief's earlier point again where I think there's a lot of potential for that one as well. >> All right, well, terrific gentlemen. Thank you so much for your insights, really fantastic hearing how this platform is really a difference in the lives of people in the Cherokee Nation. Of course, that were our guests, Kyle Hines, VP Strategic Accounts at Presidio as well as chief Chuck Hoskin Jr., the chief of the Cherokee Nation. And that's all for today's session at the 2021 AWS Global Public Sector Partner Awards, I'm your host for "theCUBE", Natalie Erlich. Thanks so much for watching. (upbeat music)

(upbeat music) >> Hello and welcome to today's session of the 2021 AWS Global Public Sector Partner Awards for this very important event, the award for best partner transformation, best energy solution. I'm your host, Natalie Erlich for theCUBE and I'm very pleased to welcome our next guests. They are Alan Henson, Senior Principal at Pariveda Solutions and Doug Priedeman, Project Engineering Manager at ExxonMobil Global Projects. Welcome to the program, so glad to have you here. >> Glad to be here. Thank you. >> Yes, thanks for having us. >> Terrific. Well, let's start with you, Doug. Can you give us a brief overview of your subsidiary for some of our audience that may not be familiar with it? And also how are you using AWS now to transform collaboration on major capital projects? >> Certainly and thank you. So as many will know ExxonMobil as a sort of a global energy provider around the world operating on six out of the seven continents. Global Projects, which is the specific subsidiary where I work, we are responsible for delivery of major capital projects to the various business units around the world. So we have the opportunity to, once approved by the business unit, to deliver on the engineering, procurement, and construction activities associated with building a new facility, if you will. And that ranges across oil and gas production, refining and chemical activities. >> Terrific. And I'd love to shift now to Alan. Could you give us an insight on DPH and your collaboration with ExxonMobil? That would be terrific. >> Happy too. We first got involved with Digital Project Home after Doug had reached out to AWS seeking ways to innovate how major capital projects look at collaboration in the engineering, procurement, and construction value chain. And we were brought in as an AWS Premier Partner to help design an uplift, a new way to facilitate that collaboration between ExxonMobil and its EPC companies. And we got involved early on in the design phase where we were in the room together putting up wire frames on the walls, walking through the processes, trying to figure out how do we streamline the process that had quite a bit of toil in it from both the combination of mixed systems to manual processes. And that's where we got involved and really helped to sketch out some of that early vision from Doug. >> Terrific. Now, Doug, how is Digital Project Home facilitating collaboration with your contractors? >> Well, as folks would recognize, some of these projects are quite large, hundreds of millions, billions of dollars, very extensive in terms of the number of people on the owner-operator side as well as the various professional contracting firms that help us to succeed at building out these projects and the decisions, the interactions, the way that we work with one another involves hundreds of millions of hours in some cases, and many, many decisions. What we were looking for is to try to understand how some of those formal interactions, where questions are asked and answered and we need a record of the question that was asked and answered for contractual purposes and for the history, when documents are submitted and need to be reviewed and returned. Some of those formal interactions, historically, had been through platforms and methodologies that were really quite, to use the phrase Alan just did, quite toilsome. And what we were looking to do was to kind of come in to the modern world and use some of the digital tools, methods and programming that are available to help automate in some cases, to help smooth the actual transfer of information, and to bring information to the surface. As practitioners on a project, how do you have information available to you at your fingertips so that you can have better information that allows you to make better decisions and return your answers, not only more quickly with less hours involved in getting to that answer, but also a better answer with a higher confidence that we've answered it the way we need to, we don't have to revisit later. >> Terrific. Well, Alan can you now describe some of the benefits of this cloud native serverless architecture? >> Absolutely. If you remember back what Doug was saying earlier, ExxonMobil operates on six to seven continents around the world. So one of the first things we wanted to do is make sure that we were designing for a solution that could meet any end-user, no matter where they were in the world, whether it was Africa, North America, Australia, Asia, it didn't matter. So we wanted to choose a cloud infrastructure like AWS that had an amazing ability to serve global customers around the world. And more specifically, we knew it was really important to get to a value adding solution as quickly as possible. So by leveraging serverless technology, we got to spend most of our time building the technology that was going to be adding value because AWS infrastructure had already solved many of just the pipe work style issues at hand. So AWS really gave us an accelerated platform to really start diving in to the innovative side of improving collaboration between ExxonMobil and their engineering, procurement and construction vendors. >> Terrific. Now staying with you, Alan. I'd love to hear how is that helping ExxonMobil to build with greater agility and at lower costs? >> There are a couple of things that come to mind with me. First, we led very early on with a modular based design. We knew there were going to be multiple use cases that we had to satisfy and every major capital project does follow rigorous global processes, but often has to adapt them to the environment at hand to what they're particularly constructing, things of that nature. So we wanted to build a solution that would adapt them quickly, so they're not constantly having to go back and build new customizations, new workflows that were specific to one entity or project versus another. So just by making it modular and flexible, we were able to already start to save costs. Additionally, because we're moving into the cloud, we completely take out a lot of the infrastructure maintenance costs that go with that. And that's really where the AWS infrastructure and the cloud based solution really started to help save money as we streamlined this solution. >> Yeah. Well, speaking of flexibility, Doug, why is it so important for your business? >> So, as Alan pointed out, Natalie, we work all over the world with different partners, different EPC contractors, and so we needed the flexibility to be able to use this tool in locations, all around the world. In many cases, the same project has people located around the world. So we had to have that speed and access. We also had to have the flexibility to be able to adjust to specific requirements perhaps of unique relationships between us, our co-venture partners, the countries that host us and so forth. But in addition to that, I'll add to Alan's comment, by structuring it the way Pariveda did, what we ended up with is sort of foundational building blocks that allowed us then to extend in future to additional interactions that we might have with our contractors. So we built out the first couple, and those are available to us today, technical queries and document reviews, but we knew and anticipate that we will continue to have additional workflows, if you will, additional interactions with our partners that we will want to automate and strengthen in the same way. And so having the flexibility of this building block architecture that Pariveda put together allows us to anticipate that in future we can build that out to additional workflows. >> Terrific. Well, now shifting gears. I'd love to hear from Alan a bit here, or actually Doug, excuse me. How do you actually find the system? Do you find that it is intuitive, or do you have to train people really meticulously on this kind of platform? >> Well, design from the beginning to be a very user-friendly. The user experience element of the design work, Pariveda brought that in from the very beginning. And in fact, from our perspective, was one of the key talents that they brought to the design. So we had a problem that we were trying to solve, a platform that we wanted it to work on, but that user interaction, that user experience was so important from the very beginning and is quite frankly, an area where I lacked the experience to have been able to influence it very much, but the Pariveda team and the AWS team as they work together with us built in user experience from the very beginning. That doesn't mean that we don't have to still give some folks a little bit of training to get used to it, but it was designed from the beginning to be quite an intuitive approach, so folks could do their work. We really were after, from my view, from the very beginning, low in toil, rich in information, those were the two things we were trying to accomplish with the entire platform. >> Yeah. And if either one of you want to jump in here. Obviously, you're dealing with a lot of information, what is the data storage like? >> It's surprising not as much as you might think. We designed for optimized data storage from the beginning. We really wanted to make sure we only stored the data that we needed, but also capture as much of it as possible so that we could surface information. That was a goal for us in the beginning, was to not only capture the information that was happening between the collaboration, but design it in a way that we could use technologies like AI and machine learning languages capabilities to surface data out. So from a data storage standpoint, a lot of the data was stored outside of AWS, but we also have a fair amount stored inside of AWS. And because of that footprint, we were able to keep costs quite low. >> Terrific. Well, Alan, again, staying with you, really curious. How is this system addressing the pain points of ExxonMobil global projects specifically? >> One of the main goals from the beginning, like Doug was saying, is to reduce the toil. And a lot of the toil came from the process of an EPC company needing to submit a document over to ExxonMobil and then getting it distributed to the right teams to provide that feedback, or perhaps in reverse, where ExxonMobil needed to send a document over to another EPC companies to get feedback as well. That oftentimes involve multiple people on both sides of that equation. It involved multiple systems that had to be accessed and leveraged to not only capture and trance to document, provide tools for doing markup and providing comments. Digital Project Home unified that entire experience so that the engineers on both sides of the document collaboration process could go into one system and perform all their functions. We automated the routing. We gave them an in tool PDF markup capabilities. So they could just load the document straight into their browser, start doing their work, add their comments, save and submit, and the system would facilitate all of that. So we took out multiple hops in the process and reduce the amount of time people had to spend doing tasks that weren't necessarily a value add. >> And I'll add to that. Natalie, is it okay I'll add to that? >> Oh, please do. >> Both on the EPC contractor side as well as the owner side, we have small teams of what we call document controllers 'cause we handle so many documents. But it's quite a labor intensive or manual type approach, but it didn't need to be. And the DPH approach and the way that it was built out, it's still not completely eliminated all of the intervention of document controllers, but it reduces the burden and even the team size necessary to maneuver those documents back and forth. We in our engagements with our contractors have a contractual obligation to return our comments within a specified period of time. And we were losing 10 to 20% of that time just in the document management side of getting it from the right person to the right person and back. And so when schedules are tight, we have a lot to do, losing 20% of our contractual time to get a document returned with comments, that was a bit painful for us. So eliminating that, or at least drastically reducing it was a big win among others. >> Well, staying with you, Doug, what do you see as the major benefits of creating this platform on AWS? >> Really, to me, it comes down to better decisions. In underpinned by better information at hand to those who are or having to review, answer questions, review documents that are information at hand that allows us then to have the information that's required to get to a good answer and provide that back, whether it's from the contractor to us or the other way around. On either side, surfacing information, because otherwise a practitioner is going off to find an industry standard, going back to find out if we already had a query on that same document, see what we said last time or how that question was different from this question. There was a lot of hunting and pecking, so to speak to find out what information was allied to the question or allied to the document. And what we were really looking for was a solution that would bring that information up, give us live links, allow us to jump across to that information straight away. Not only have the information, but also be able to access it quite quickly. >> Terrific. And Alan, now shifting gears over to you. I'm really curious how this system will improve efficiencies for MCPs for the years to come. >> As Doug mentioned, we designed the system from the beginning to be extendable, to be modular, to think of like Lego blocks, where the Legos themselves represent functionality that we know can serve purposes in multiple different workflows. So as ExxonMobil continues to develop this platform in partnership with feedback from their engineering, procurement, and construction companies, they're going to be able to quickly build new workflows leveraging component based design that we did from day one. So the efficiency is going to come as they or able to add new capabilities to the platform very quickly and using modern technology to ensure that it's relevant and capable and serving the businesses needs. >> Terrific. Now, Doug, as this project scales up, what are some of the other benefits would you expect can be realized? >> Well, Natalie, we're looking to extend it to more projects as is often the case with things like this. We trial it in a few places to get, to build it out, gain the experience. We're looking to extend it to additional users, but we're also looking to do, just what Allan was just mentioning there, folks involved in major projects are familiar with such things as management of change, deviations, issues management. So there are a handful of interactions that happen between between parties and something like this. And so while we've built out two of the workflows as a starting place, and while we've deployed this tool, if you will to a few of our projects, our vision is that we would be able to extend the number of users and be able to build out additional important interactions or workflows that we have so that the Digital Project Home becomes a place that holds even more of a practitioners daily work activities. >> Terrific. And if either one of you would like to jump in here and provide just like a quick snapshot of how much manpower, time, and costs are saved as a result of using this type of platform. >> Well, on our side, Alan, I'll jump in here. We anticipate on a large project, we will transact over thousands of documents. Now, some of them get more review and some of them get less review, but there are thousands of documents that are developed in terms of engineering, procurement, and construction type activities. And to the extent that we can save a small amount of time and get better answers on each one, that really adds up quickly when you consider the number of hours expended in that overall effort. So we're talking thousands upon thousands of hours that we believe can be reduced and what that translates to, not only the ability to execute a project with a smaller team, but we are confident with better information in hand, we'll make better decisions. >> Well, thank you both for your insights. Loved having you on this program. That was Alan Henson, Senior Principal at Pariveda Solutions and Doug Priedeman, Project Engineering Manager at ExxonMobil Global Projects. That's all for this session for the 2021 AWS Global Public Sector Partner Awards, and I'm your host Natalie Erlich for theCUBE. Thanks so much for watching. (bright music)

(upbeat music) >> Welcome to the special CUBE presentation of the AWS Global Public Sector Partner Awards Program. I'm here with the leader of the partner program, Sandy Carter, Vice President, AWS, Amazon Web Services @Sandy_Carter on Twitter, prolific on social and great leader. Sandy, great to see you again. And congratulations on this great program we're having here. In fact, thanks for coming out for this keynote. Well, thank you, John, for having me. You guys always talk about the coolest thing. So we had to be part of it. >> Well, one of the things that I've been really loving about this success of public sector we talked to us before is that as we start coming out of the pandemic, is becoming very clear that the cloud has helped a lot of people and your team has done amazing work, just want to give you props for that and say, congratulations, and what a great time to talk about the winners. Because everyone's been working really hard in public sector, because of the pandemic. The internet didn't break. And everyone stepped up with cloud scale and solve some problems. So take us through the award winners and talk about them. Give us an overview of what it is. The criteria and all the specifics. >> Yeah, you got it. So we've been doing this annually, and it's for our public sector partners overall, to really recognize the very best of the best. Now, we love all of our partners, John, as you know, but every year we'd like to really hone in on a couple who really leverage their skills and their ability to deliver a great customer solution. They demonstrate those Amazon leadership principles like working backwards from the customer, having a bias for action, they've engaged with AWS and very unique ways. And as well, they've contributed to our customer success, which is so very important to us and to our customers as well. >> That's awesome. Hey, can we put up a slide, I know we have slide on the winners, I want to look at them, with the tiles here. So here's a list of some of the winners. I see a nice little stars on there. Look at the gold star. I knows IronNet, CrowdStrike. That's General Keith Alexander's company, I mean, super relevant. Presidio, we've interviewed them before many times, got Palantir in there. And is there another one, I want to take a look at some of the other names here. >> In overall we had 21 categories. You know, we have over 1900 public sector partners today. So you'll notice that the awards we did, a big focus on mission. So things like government, education, health care, we spotlighted some of the brand new technologies like Containers, Artificial Intelligence, Amazon Connect. And we also this year added in awards for innovative use of our programs, like think big for small business and PTP as well. >> Yeah, well, great roundup, they're looking forward to hearing more about those companies. I have to ask you, because this always comes up, we're seeing more and more ecosystem discussions when we talk about the future of cloud. And obviously, we're going to, you know, be at Mobile World Congress, theCUBE, back in physical form, again, (indistinct) will continue to go on. The notion of ecosystem is becoming a key competitive advantage for companies and missions. So I have to ask you, why are partners so important to your public sector team? Talk about the importance of partners in context to your mission? >> Yeah, you know, our partners are critical. We drive most of our business and public sector through partners. They have great relationships, they've got great skills, and they have, you know, that really unique ability to meet the customer needs. If I just highlighted a couple of things, even using some of our partners who won awards, the first is, you know, migrations are so critical. Andy talked at Reinvent about still 96% of applications still sitting on premises. So anybody who can help us with the velocity of migrations is really critical. And I don't know if you knew John, but 80% of our migrations are led by partners. So for example, we gave awards to Collibra and Databricks as best lead migration for data as well as Datacom for best data lead migration as well. And that's because they increase the velocity of migrations, which increases customer satisfaction. They also bring great subject matter expertise, in particular around that mission that you're talking about. So for instance, GDIT won best Mission Solution For Federal, and they had just an amazing solution that was a secure virtual desktop that reduced a federal agencies deployment process, from months to days. And then finally, you know, our partners drive new opportunities and innovate on behalf of our customers. So we did award this year for P to P, Partnering to Partner which is a really big element of ecosystems, but it was won by four points and in quizon, and they were able to work together to implement a data, implement a data lake and an AI, ML solution, and then you just did the startup showcase, we have a best startup delivering innovation too, and that was EduTech (indistinct) Central America. And they won for implementing an amazing student registration and early warning system to alert and risks that may impact a student's educational achievement. So those are just some of the reasons why partners are important. I could go on and on. As you know, I'm so passionate about my partners, >> I know you're going to talk for an hour, we have to cut you off a little there. (indistinct) love your partners so much. You have to focus on this mission thing. It was a strong mission focus in the awards this year. Why are customers requiring much more of a mission focused? Is it because, is it a part of the criteria? I mean, we're seeing a mission being big. Why is that the case? >> Well, you know, IDC, said that IT spend for a mission or something with a purpose or line of business was five times greater than IT. We also recently did our CTO study where we surveyed thousands of CTOs. And the biggest and most changing elements today is really not around the technology. But it's around the industry, healthcare, space that we talked about earlier, or government. So those are really important. So for instance, New Reburial, they won Best Emission for Healthcare. And they did that because of their new smart diagnostic system. And then we had a partner when PA consulting for Best Amazon Connect solution around a mission for providing support for those most at risk, the elderly population, those who already had pre existing conditions, and really making sure they were doing what they called risk shielding during COVID. Really exciting and big, strong focus on mission. >> Yeah, and it's also, you know, we've been covering a lot on this, people want to work for a company that has purpose, and that has missions. I think that's going to be part of the table stakes going forward. I got to ask you on the secrets of success when this came up, I love asking this question, because, you know, we're starting to see the playbooks of what I call post COVID and cloud scale 2.0, whatever you want to call it, as you're starting to see this new modern era of success formulas, obviously, large scale value creation mission. These are points we're hearing and keep conversations across the board. What do you see as the secret of success for these parties? I mean, obviously, it's indirect for Amazon, I get that, but they're also have their customers, they're your customers, customers. That's been around for a while. But there's a new model emerging. What are the secrets from your standpoint of success? you know, it's so interesting, John, that you asked me this, because this is the number one question that I get from partners too. I would say the first secret is being able to work backwards from your customer, not just technology. So take one of our award winners Cognizant. They won for their digital tolling solution. And they work backwards from the customer and how to modernize that, or Pariveda, who is one of our best energy solution winners. And again, they looked at some of these major capital projects that oil companies were doing, working backwards from what the customer needed. I think that's number one, working backwards from the customer. Two, is having that mission expertise. So given that you have to have technology, but you also got to have that expertise in the area. We see that as a big secret of our public sector partners. So education cloud, (indistinct) one for education, effectual one for government and not for profit, Accenture won, really leveraging and showcasing their global expansion around public safety and disaster response. Very important as well. And then I would say the last secret of success is building repeatable solutions using those strong skills. So Deloitte, they have a great solution for migration, including mainframes. And then you mentioned early on, CloudStrike and IronNet, just think about the skill sets that they have there for repeatable solutions around security. So I think it's really around working backwards from the customer, having that mission expertise, and then building a repeatable solution, leveraging your skill sets. >> That's a great formula for success. I got you mentioned IronNet, and cybersecurity. One of things that's coming up is, in addition to having those best practices, there's also like real problems to solve, like, ransomware is now becoming a government and commercial problem, right. So (indistinct) seeing that happen a lot in DC, that's a front burner. That's a societal impact issue. That's like a cybersecurity kind of national security defense issue, but also, it's a technical one. And also public sector, through my interviews, I can tell you the past year and a half, there's been a lot of creativity of new solutions, new problems or new opportunities that are not yet identified as problems and I'd love to get your thoughts on my concern is with Jeff Bar yesterday from AWS, who's been blogging all the the news and he is a leader in the community. He was saying that he sees like 5G in the edge as new opportunities where it's creative. It's like he compared to the going to the home improvement store where he just goes to buy one thing. He does other things. And so there's a builder culture. And I think this is something that's coming out of your group more, because the pandemic forced these problems, and they forced new opportunities to be creative, and to build. What's your thoughts? >> Yeah, so I see that too. So if you think about builders, you know, we had a partner, Executive Council yesterday, we had 900, executives sign up from all of our partners. And we asked some survey questions like, what are you building with today? And the number one thing was artificial intelligence and machine learning. And I think that's such a new builders tool today, John, and, you know, one of our partners who won an award for the most innovative AI&ML was Kablamo And what they did was they use AI&ML to do a risk assessment on bushfires or wildfires in Australia. But I think it goes beyond that. I think it's building for that need. And this goes back to, we always talk about #techforgood. Presidio, I love this award that they won for best nonprofit, the Cherokee Nation, which is one of our, you know, Native American heritage, they were worried about their language going out, like completely out like no one being able to speak yet. And so they came to Presidio, and they asked how could we have a virtual classroom platform for the Cherokee Nation? And they created this game that's available on your phone, so innovative, so much of a builder's culture to capture that young generation, so they don't you lose their language. So I do agree. I mean, we're seeing builders everywhere, we're seeing them use artificial intelligence, Container, security. And we're even starting with quantum, so it is pretty powerful of what you can do as a public sector partner. >> I think the partner equation is just so wide open, because it's always been based on value, adding value, right? So adding value is just what they do. And by the way, you make money doing it if you do a good job of adding value. And, again, I just love riffing on this, because Dave and I talked about this on theCUBE all the time, and it comes up all the time in cloud conversations. The lock in isn't proprietary technology anymore, its value, and scale. So you starting to see builders thrive in that environment. So really good points. Great best practice. And I think I'm very bullish on the partner ecosystems in general, and people do it right, flat upside. I got to ask you, though, going forward, because this is the big post COVID kind of conversation. And last time we talked on theCUBE about this, you know, people want to have a growth strategy coming out of COVID. They want to be, they want to have a tail win, they want to be on the right side of history. No one wants to be in the losing end of all this. So last year in 2021 your goals were very clear, mission, migrations, modernization. What's the focus for the partners beyond 2021? What are you guys thinking to enable them, 21 is going to be a nice on ramp to this post COVID growth strategy? What's the focus beyond 2021 for you and your partners? >> Yeah, it's really interesting, we're going to actually continue to focus on those three M's mission, migration and modernization. But we'll bring in different elements of it. So for example, on mission, we see a couple of new areas that are really rising to the top, Smart Cities now that everybody's going back to work and (indistinct) down, operations and maintenance and global defense and using gaming and simulation. I mean, think about that digital twin strategy and how you're doing that. For migration, one of the big ones we see emerging today is data-lead migration. You know, we have been focused on applications and mainframes, but data has gravity. And so we are seeing so many partners and our customers demanding to get their data from on premises to the cloud so that now they can make real time business decisions. And then on modernization. You know, we talked a lot about artificial intelligence and machine learning. Containers are wicked hot right now, provides you portability and performance. I was with a startup last night that just moved everything they're doing to ECS our Container strategy. And then we're also seeing, you know, crippin, quantum blockchain, no code, low code. So the same big focus, mission migration, modernization, but the underpinnings are going to shift a little bit beyond 2021. >> That's great stuff. And you know, you have first of all people don't might not know that your group partners and Amazon Web Services public sector, has a big surface area. You talking about government, health care, space. So I have to ask you, you guys announced in March the space accelerator and you recently announced that you selected 10 companies to participate in the accelerated program. So, I mean, this is this is a space centric, you know, targeting, you know, low earth orbiting satellites to exploring the surface of the Moon and Mars, which people love. And because the space is cool, let's say the tech and space, they kind of go together, right? So take us through, what's this all about? How's that going? What's the selection, give us a quick update, while you're here on this space accelerated selection, because (indistinct) will have had a big blog post that went out (indistinct). >> Yeah, I would be thrilled to do that. So I don't know if you know this. But when I was young, I wanted to be an astronaut. We just helped through (indistinct), one of our partners reach Mars. So Clint, who is a retired general and myself got together, and we decided we needed to do something to help startups accelerate in their space mission. And so we decided to announce a competition for 10 startups to get extra help both from us, as well as a partner Sarafem on space. And so we announced it, everybody expected the companies to come from the US, John, they came from 44 different countries. We had hundreds of startups enter, and we took them through this six week, classroom education. So we had our General Clint, you know, helping and teaching them in space, which he's done his whole life, we provided them with AWS credits, they had mentoring by our partner, Sarafem. And we just down selected to 10 startups, that was what Vernors blog post was. If you haven't read it, you should look at some of the amazing things that they're going to do, from, you know, farming asteroids to, you know, helping with some of the, you know, using small vehicles to connect to larger vehicles, when we all get to space. It's very exciting. Very exciting, indeed, >> You have so much good content areas and partners, exploring, it's a very wide vertical or sector that you're managing. Is there any pattern? Well, I want to get your thoughts on post COVID success again, is there any patterns that you're seeing in terms of the partner ecosystem? You know, whether its business model, or team makeup, or more mindset, or just how they're organizing that that's been successful? Is there like a, do you see a trend? Is there a certain thing, then I've got the working backwards thing, I get that. But like, is there any other observations? Because I think people really want to know, am I doing it right? Am I being a good manager, when you know, people are going to be working remotely more? We're seeing more of that. And there's going to be now virtual events, hybrid events, physical events, the world's coming back to normal, but it's never going to be the same. Do you see any patterns? >> Yeah, you know, we're seeing a lot of small partners that are making an entrance and solving some really difficult problems. And because they're so focused on a niche, it's really having an impact. So I really believe that that's going to be one of the things that we see, I focus on individual creators and companies who are really tightly aligned and not trying to do everything, if you will. I think that's one of the big trends. I think the second we talked about it a little bit, John, I think you're going to see a lot of focus on mission. Because of that purpose. You know, we've talked about #techforgood, with everything going on in the world. As people have been working from home, they've been reevaluating who they are, and what do they stand for, and people want to work for a company that cares about people. I just posted my human footer on LinkedIn. And I got my first over a million hits on LinkedIn, just by posting this human footer, saying, you know what, reply to me at a time that's convenient for you, not necessarily for me. So I think we're going to see a lot of this purpose driven mission, that's going to come out as well. >> Yeah, and I also noticed that, and I was on LinkedIn, I got a similar reaction when I started trying to create more of a community model, not so much have people attend our events, and we need butts in the seats. It was much more personal, like we wanted you to join us, not attend and be like a number. You know, people want to be part of something. This seem to be the new mission. >> Yeah, I completely agree with that. I think that, you know, people do want to be part of something and they want, they want to be part of the meaning of something too, right. Not just be part of something overall, but to have an impact themselves, personally and individually, not just as a company. And I think, you know, one of the other trends that we saw coming up too, was the focus on technology. And I think low code, no code is giving a lot of people entry into doing things I never thought they could do. So I do think that technology, artificial intelligence Containers, low code, no code blockchain, those are going to enable us to even do greater mission-based solutions. >> Low code, no code reduces the friction to create more value, again, back to the value proposition. Adding value is the key to success, your partners are doing it. And of course, being part of something great, like the Global Public Sector Partner Awards list is a good one. And that's what we're talking about here. Sandy, great to see you. Thank you for coming on and sharing your insights and an update and talking more about the 2021, Global Public Sector partner Awards. Thanks for coming on. >> Thank you, John, always a pleasure. >> Okay, the Global Leaders here presented on theCUBE, again, award winners doing great work in mission, modernization, again, adding value. That's what it's all about. That's the new competitive advantage. This is theCUBE. I'm John Furrier, your host, thanks for watching. (upbeat music)

>>from around the >>globe. It's the Cube with digital coverage of AWS reinvent 2020. Special coverage sponsored by AWS Worldwide Public sector. >>Right. Hello and welcome to the Cube. Virtual our coverage of aws reinvent 2020 with special coverage of the public sector experience. This is the day when we go through all the great conversations around public sector in context to reinvent great guest will for Justin, head of A W s ai and machine learning enablement and partnership with AWS Wilfred. Thanks for joining us. >>Thanks, John. Thanks for having me on. I'm pretty excited to be part of this cube interview. >>Well, I wish we could be in person, but with the pandemic, we gotta do the remote. But I want to get into some of the things you're working on. The A I m l Rapid Adoption Assistance Initiative eyes a big story. What is? What is it described what it is. >>So we launched this artificial intelligence slash machine learning rapid adoption assistance for all public sector partners who are part of the AP in network in September 2020. Onda. We launched this in response to the president's Executive water called the American Year Initiative. So the rapid adoption assistant what it provides us. It provides a direct scalable on automated mechanism for all the public sector partners to reach out to AWS experts within our team for assistance in building and deploying machine learning workloads on behalf of the agencies. So for all all the partners who are part off, this rapid adoption assistance will go through a journey with AWS with my team and they will go through three different faces. The first face will be the envisioning face. The second phase would be the enablement face on the third would be the bill face, as you know, in the envisioning face will dive deeply The use case, the problem that they're trying to solve. This is where we will talk about the algorithms and framework on. We will solidify the architecture er on validate the architecture er on following that will be an enablement face where we engage with the partners trained their technical team, meaning that it will be a hands on approach hands on on keyboard kind of approach where we trained them on machine learning stack On the third phase would be the bill face on the partners leverage the knowledge that they have gained through the enablement and envisioning face, and they start building on rolling out workloads on behalf of the agencies. So we will stay with them throughout the journey on We will doom or any kind of blockers be technical or business, so that's a quick overview off a more rapid adoption assistance program. >>It's funny talking to Swami over the years and watching every year at reinvent the A I. M L Portfolio. Dr Matt Wood is always doing something new. This year is no exception. Even Mawr Machine Learning and AI in the In the News on this rapid adoption assistant initiative sounds like it's an accelerant. Um, so I get all that, But I want to ask you, what problem does it solve for the customer? Or Amazon is because there's demand. There's too much demand. People wanna go faster. What problem does this initiative this rapid adoption of a I machine learning initiative solved? >>So as you know, John, artificial intelligence and related technologies like deep learning and machine learning can literally transform the way agencies operate. They can enable them to provide better services, quicker services and more secure services to the citizens of this country. And that's the reason the president released an executive water called American Initiative on it drives all the government agencies, specifically federal agencies, to promote artificial intelligence to protect and improve the security and economy of the nation. So if you think about it, the best way to achieve the goal is to enable the partners toe build workloads on behalf of agencies, because when it comes to public sector, most of the workloads are delivered by partners. So the problem that we face based on our interaction with the partners is that though the partners have been building a lot off applications with AWS for more than a decade, when it comes to artificial intelligence, they have very limited resources when it comes to deep learning and machine learning, right, like speech recognition, cognitive computing, national language frosting. So we wanted exactly address that. And that's the problem you're trying to solve by launching this rapid adoption assistance, which is nothing but a dry direct mechanism for partners to reach our creative, these experts to help them to build those kind of solutions for the government. >>You know, it's interesting because AI and machine learning it's a secret sauce for workload, especially modern workloads. You mentioned agencies and also public sector. You know, we've seen Certainly there's been pandemic a ton of focus on moving faster, right? So getting those APS out quickly ai drives a lot of that, so totally get it. Um, I think it's an accelerant great program. It just makes a lot of sense. And I know you guys have been going in tow by vertical and kind of having stage making all these other tools kind of be specialized within those verticals. So it makes a ton of sense. I get it, and it is a great, great initiative and solve the problem. The question I have is who gets access to this, right? Is it just agencies you mentioned? Is it all public sector? Could you just clarify who can apply to this program? >>Yes, it is a partner focused program. So all the existing partners, though it is going to affect the end agencies, were trying to help the agency's through the partners. So all the existing AP in partners who are part of the PSP program, we call it the public sector partner program can apply for this rapid adoption assistance. So you have been following John, you have been following AWS and AWS partners on a lot of partners have different kind of expertise on they. They show that by achieving a lot of competencies, right, it could be technical competencies like big data storage and security. Or it could be domain specific competencies like public safety education on government competency. But for a playing this program, the partners don't need to have any kind of competency, and all they have to have is they have to be part of the Amazon Partner Network on they have to be part of the public sector partner program. That is number one Second. It is open toe all partners, meaning that it is open toe. Both technology partners, as well as consulting partners Number three are playing is pretty simple, John, right? You can quickly search for a I M or rapid adoption assistance on a little pop up a page on a P network, the partners have to go on Phil pretty basic information about the workload, the problem that they're trying to solve the machine learning services that they're planning to use on a couple of other information, like contact information, and then our team reaches out to the partner on help them with the journey. >>So real. No other requirements are prerequisites. Just part of the partner program. >>Absolutely. It is meant for partners. And all you have to do is you have to be a part off 18 network, and you have to be a public sector apartment. >>Public sector partner makes sense. I mean, how you're gonna handle the demand. I'm sure the it's gonna be a tsunami of interest, because, I mean, why wouldn't someone take advantage of this? >>Yep. It is open to all kinds of partners because they have some kind of prerequisites, right? So that's what I'm trying to explain. It is open to all partners, but we have since it is open to existing partners, we kind of expect the partners toe understand the best practices off deploying a machine, learning workloads, or for that case, any kind of workload which should be scalable, land secure and resilient. So we're not going to touch? Yeah, >>Well, I wanna ask you what's what's the response been on this launch? Because, you know, I mean to me, it just makes it's just common sense. Why wouldn't someone take advantage of it? E. Whether responses partner or you have domain expertise or in a vertical just makes a lot of sense. You get access to the experts. >>The response has been great. As I said, the once you apply the journey takes six weeks, but already we just launched it. Probably close toe. Two months back in September 2nd week of September, it is almost, uh, almost two months, and we have more than 15 partners as part of this program on dykan name couple of partners say, for example, we worked with delight on We Are. We will be working on number of work clothes for the Indy agencies through delight. And there are other couple of number of other partners were making significant progress using this rapid adoption assistance that includes after associates attained ardent emcee on infinitive. So to answer your question, the response has been great so far. >>So what's the I So I gotta ask, you know, one of things I thought that Teresa Carlson about all the time in Sandy Carter is, you know, trying to get the accelerant get whether it's Fed ramp and getting certifications. I mean, you guys have done a great job of getting partners on board. Is there any kind of paperwork? What's the process? What should a partner expect to take advantage of that? I'm sure they'll be interest beyond just the launch. What's what's involved? What zit Web bases it check a form? Is that a lot of hoops to jump through? Explain what? What? The process >>is. Very interesting question. And it probably is a very important question from a part of perspective, right? So since it is offered for a peon partners, absolutely, they should have already gone through the AP in terms and conditions they should have. Already, a customer agreement or advanced partners might have enterprise agreement. So for utilizing this for leveraging this rapid adoption assistance program, absolutely. There's no paperwork involved. All they have to do is log into the Web form, fill up the basic information. It comes to us way, take it from there. So there is no hard requirements as long as you're part of the AP network. And as long as you're part of the PSP program, >>well, for great insight, congratulations on a great program. I think it's gonna be a smash hit. Who wouldn't wanna take? I know you guys a lot of goodness there with Amazon Cloud higher level services with a I machine learning people could bring it into the table. I know from a cybersecurity standpoint to just education the range of, um, workloads is gonna be phenomenal. Obviously military as well. Eso totally cool. Love it. Congratulations. Like my final question is, um, one about the partner. So I'm a partner. I like this. Say I'm a partner. I jump in Easy to get in. Walk me through What happens? I mean, I signed some paperwork. You check the boxes, I get involved, I get, like, a rep. Do I do things? Do I? What happens to me? Walk me down the path of execution. What's expectation of what will happen? >>I'll explain that in two parts, John. Right? One is from a partner journey perspective and then from AWS perspective. What? What we expect out off partners, right? So, from a experience perspective, as long as they fill out, fill out the web form on, fill out the basic information about the project that they're trying to work. It comes to us. The workflow is automated. All the information is captured on the information comes to my team on. We get back to the partners within three days, but the journey itself can take from 6 to 8 weeks because, as I mentioned during the envisioning case, we try to map the problem to the solution. But the enablement phases the second phase is where it can take anywhere from 2 to 3 weeks because, as I mentioned, we focused on the three layers of the machine learning stack for certain kind of partners. They might be interested in sage maker because they might want to build a custom machine learning model. But for some of the partners, they want the argument that existing applications using S. R or NLP or nL you so we can focus on the high level services. Or we can train them on stage makers so it can take anywhere between 2 to 3 weeks or 3 to 4 weeks. And finally, the build phase varies from partner to partner on the complexity of the work. Lord at that point were still involved with a partner, but the partner will be taking the lead on will be with them to remove any kid of Glaucus being technical or, uh, business couple of Yeah, well, I just >>want to say the word enablement in your title kind of speaks volumes. This isn't about enabling customers. >>It is all about enabling the in customers through partners. So we focus on enabling partners. They could be business big system integrators like Lockheed's or Raytheon's or Delight. Or it could be nimble in small partners. Or it could be a technology partner building an entire pass or SAS service on behalf of the government agencies. Right or that could help the comment agencies in different verticals. So we just enabled the in the agency's through the partners. And the focus of this program is all about partner enablement. >>Well, for just ahead of a does a i machine learning enablement in partnership, part of public sector with a W. S. This is our special coverage. Well, for thanks for coming on being a cube virtual guest. I wish we could be in person, but this year it's remote. This is the cube virtual. I'm John for a year. Host of the Cube. Thanks for watching. >>Thanks a lot, John.

>> From around the globe, it's theCUBE with digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS Worldwide Public Sector. >> Hello, welcome back to theCUBES coverage, of AWS re:Invent 2020 virtual. This is theCUBE virtual, I'm John Furrier, your host. We're not there in person this year because of the pandemic, but we're doing the remote. This is special coverage of the public sector, we got two great guests, Manpreet Mattu, who was the Worldwide Public Sector of Startups and Venture Capital team with AWS, and Michael Jackson who's the leader, general manager of Public Health and Venture Capital and Startups. Gentlemen, thanks for joining me. Thanks for coming up. >> Okay, it's my pleasure, thanks for having. >> I loved love welcome to theCUBE. I just want to say that Amazon never forgets the startups, that's where are they were born and bred it's been a startup. It's always day one as the expression goes, but truly even with the success, not just in the enterprise and starts within public sector, it's still a startup agility mindset, just want to call that out and say congratulations. Okay, let's get into it. Tell us about your roles and your backgrounds and why you're here. >> So, I believe so, I'm the head of AWS Public Sector, VC and Startups team, and our mission really is to help our public sector customers, adopt innovation that is built by the startups. I've been with AWS for about two and a half years. And prior to that, I was in a similar role with Booz Allen, helping our public sector customers, adopt innovation data as well. >> Michael. >> Yeah, so I am the general manager of Public Health, for on the Venture Capital and Startups team. My career here at AWS began just over four years ago. I was brought on to the state and local government team, initially building the public health practice from inception, and I also built and led our U S elections business. And I'm really excited now to transition into this global role, to lead our public health VC and startups practice, and really democratize access to innovation for our startups in the healthcare space. >> Well, great journey. You guys are converging, the VC and startup teams are coming together. A lot of macro trends certainly are tailwinds for you guys. Obviously, the pandemic is forcing, more accelerated modern applications in public sector, and we've been covering more and more success stories, of the change happening quickly. As access to capital continues to be great, and agility with the cloud, how has that impacted your teams and your approach? Can you guys share how that's changed this year? Because there's more pressure now to be digital, there's more opportunities, there's more still capital flowing, how has it impacted your roles? >> Now, so at the very high level, Amazon invests in companies because, we want those companies to be successful. And AWS itself makes a substantial investment, in agility, the startup customers success. We have things like service credits and things like, business nurturing programs that we have built over the course of the last seven, eight years. For example, over the past, you had a loan, Amazon has provided more than a billion dollars in credits, through AWS Activate program, to help startups grow and scale their businesses. And not only that a total of more than three and a half billion dollars in credit to more than 140,000 startups, over the last seven years, all through the course of the Activate program. From more so, on the healthcare side, I would want, certainly MJ to also, speak through or speak to, the challenges that the health system has faced in the COVID times, and how AWS is helping the provider, healthcare providers and the startups, really achieve success, and help the patient populations on that note. >> Michael, weighing on this new programs, you guys are launching in the impact healthcare, I see where we're seeing the frontline workers, I mean, it's everyone seeing it on TV and the newspaper, and it's impacting friends and family, give us the update. >> Absolutely, so we're here today to launch a new program. We call it the Healthcare Acceleration program. And basically, there are two halves to the program, with an undercurrent or a recurring undercurrent, I should say. Just really quickly before I touch on that though, I'd be remissed if I didn't make note of the fact that, you're right capital is still flowing, and it's a really big deal particularly, as healthcare and public health becomes such a priority, but one of the strategic imperatives of our team's role, similar to the way we democratize access to innovation for startups, we also find it really important to democratize access, to resources for founders, underrepresented founders, so, that everyone can have a level playing field, and equal access to those resources and funding, and things of that nature. Getting back to some of the healthcare priorities, in particular, I don't have to tell you about, this pandemic where on the third, and possibly the deadliest wave losing over 1000 Americans per day. And so, not only are we interested in helping our customers, our enterprise customers inject innovation from startups so that they can address clinical aspects, of the pandemic and beyond, but there are underlying rippling societal implications as well. Things that have been exacerbated by the pandemic. Things like mental health, behavioral health, including substance use abuse, clinical clinician burnout, things like social determinants of health, which lead to disproportionately impacted demographics. So, there's a whole lot to unpack and I'm sure we will, but at the highest level, that's what we're looking to help, our enterprise customers address, with the help of our innovative high potential startups. >> I mean, strategic focus, just go a little bit further on how important this is, because, programs are needed, there is burnout, okay. >> Yeah. >> You have mental health, physical health, everything in between. What are you guys launching? What's new? What can people take away right now from AWS, and what startups and when, 'cause a lot of people are changing their focus. I was seeing people leave their jobs, to have to get on this new mission. They're seeing the pain, there's a lot of entrepreneurial energy, happening right now here. Go further, please. >> So, you touched right on it. So, there are two sides. I mentioned there are two halves, and an underlying current, right? So, the two halves are the supply and the demand. The supply side is what we refer to as the startups, vetted high potential, high growth startups, in the health tech space, that we can help to accelerate their go to market, right? We can pair them with mentorship, credits, we call it the 4Cs. There's capital, mapping them potentially to investors, who are interested into accelerating their growth. There's code, technical support, whether it's cloud formation templates, or technical expertise, connections such as other startups, incubators, accelerators, etcetera, and finally mapping them to customers. So, that's, what's in it for the startups. And then on the other side, the enterprise side, again, there are so many enterprises from payers to providers and others who are looking to accelerate their efforts, to digitally transform their enterprise. And so, by partnering with AWS, and the Healthcare Acceleration program, they can trust that there are AWS powered startups, that are vetted and prepared, to inject that sense of urgency, that sense of innovation. And the underlying current, the dots that are being connected is, workforce modernization or economic development, because in many cases, you're right, people are losing their jobs, people are looking at ways that they can, modernize the workforce is locally leverage local talent. And so, entrepreneurship is a great way, to stimulate the local economy, and help older workers or workers who are looking to transition into a more relevant occupations, to do just that. So, this is an all encompassing program. >> Let's get into this health accelerator from AWS. This is something that is on the table, AWS Health Accelerator, who are the stakeholders, and what are the benefits of this program? >> Well, I mean, before we actually, go to the accelerator for me, I think there's this focus on the healthcare, as an industry, as a vertical, is very important to talk about. The industry is experiencing transformation. It is experiencing disruption and the COVID-19 pandemic, has only accelerated that. If you made, it has sort of magnified some of the stressors, which were already there in the system. If you combine that with the sort of the undercurrent that MJ mentioned from a technological perspective, the delivery of healthcare globally is going digital. So, you see technology is like artificial intelligence, machine learning, big data, augmented reality, IoT based variables. All of these technologies are coming together, to enable applications, such as remote diagnostics, patient monitoring, predictive prescriptive healthcare. And we truly feel that this presents a tremendous opportunity to improve the patient experience, and more importantly, the patient outcomes, using these technologies, and these newly enabled applications through those technologies. And as an example, in the U S alone, there are 22 key healthcare AI use cases, that are projected to grow by, or to approximately around $22 billion by 2025. So, in AWS, we are collaborating with the wide spectrum of healthcare providers, with public health organizations, with government agencies, all around the globe to support their effort, to cope with the rippling effects of the COVID-19. And arguably, many of them are visible to us today, but I would argue that many many are not even yet, have been begun to understand by us and by our customers. So, that is the reason why we want to put some emphasis, on healthcare from a public sector standpoint. >> Yeah, that's a great call-out Manpreet, I want to just highlight that, maybe get an additional commentary because, the old days it was just the institution, the hospital and then you're done. And then it was okay, hospital plus the caregiver, the doctors, and the workers, and now the patient. So, holistically, you're calling out the big picture, the patient care, right. Their families, their environment, the caregivers, and the institution, and now the supply chain, all of it integrated together. That's where the action is. And that's where the data comes in, that's where cloud scale can come in. Is that right? Am I getting that right there? >> Yeah, that's absolutely. I'm sorry Manpreet. >> Welcome MJ, go on. >> I was going to say you're absolutely right. In fact, we like to look at it almost like a bullseye, right? So, at the center of the bullseye, like you said, usually, the first stakeholder that comes to mind, is the provider or the coordinator of care. Outside of there, you have the payer, outside of there, you have researchers. And in any even further outside still are your regulators, your healthcare agencies at the local state, and federal levels, including military health. So, it's a rippling effect of customers on that side, as well as you asked about stakeholders on the startup side, there's also a bullseye of influence. Starting with the founder herself, the founder, and her executive team, moving out from there to the startup, as an organization outside from there, we've got incubators and accelerators that are in place, to help accelerate that growth as well. And then farther out you've got investors, VCs, and investors, and so on both sides, supply and demand we're looking to tap into, and accelerate the growth, and make connections between the two. >> Yeah, (indistinct) but when I, in back in real life, when we used to go to games, you walk into the stadium, you buy your ticket with your phone, you go to your seat, concessions guys, deliver things there for you, the fan experience, the players are there. I mean, why can't we have that in healthcare? I was just everything is happening, right. Go for good, yeah. And I think that's the Nirvana, hopefully soon. >> We're working on it. >> Good stuff. I know, I just love the vision, I think is so relevant and super important. Now, let's get into this health accelerator. What's this all about? Let's get into that. >> So, the health accelerator will be, a multi-week on-demand program. Where we're going to map high potential vetted startups, to a number of resources, right. I mentioned before that there will be mentorship, there will be technical experts who will be able to, take these startups who have established some presence, but we want to accelerate their ability to go deeper specifically into public health, throughout that ecosystem that I just described, right? Starting with providers and coordinators, payers, researchers, regulators. We want to give them a way to go deep into this, heavily regulated industry, so that they can not only have access to the innovation that many startups would not otherwise, like Manpreet mentioned machine learning AI, but they also have access to the resources, to ensure their success. >> What kind of problems are you guys trying to solve with this? I mean, is there a specific vetting process, is there a criteria? Is there a bar to all over share some specifics? >> Yeah, absolutely. So, for the past few years, a lot of the major change challenges, for our public health customers have been the same, but they require a new approach. And I like to call our approach the HIGH FIVE. So, some of those challenges that have been traditionally, lingering for the past few years, equal social determinants of health. Social determinants, when we talk about that, we not only refer to the nonclinical contributors to a person's overall wellness. So, you think about issues like food deserts or recidivism homelessness, all of that transportation to access to care, right, all of that contributes. But then there's also disparities and health outcomes. When you think about socioeconomic differences, rural health, ethnic and racial minorities, so, that all factors into social determinants of health. Then there's also aging. Now, these are the strategic pillars that we like to focus on, or that we are focusing on. When I mentioned aging every day in the U S, 10,000 people celebrate their 65th birthday. Many of those individuals are suffering from comorbidities, from hypertension, diabetes, cancer, and now the lingering impact of COVID-19. And so, as these aging individuals continue to live longer, the goal is to improve the quality of their life as well. And so, many of them look to technology to age independently at home, etcetera. So, that's our second strategic pillar. The third, is mental and behavioral health. So, when I talk about mental health, I mean, everything from mild depression, all the way through suicide prevention, and especially these days with COVID-19, we see a lot of clinicians suffering from burnout. And so, it's important, that we take care of the frontline workers, those healthcare providers, and even outside of COVID-19, you think about the ways that the patient population, has continued to expand, and the growth within the provider market has not, or the pool of providers has not nearly expanded at the same rate. We've got people living longer, we've got more people than ever insured. And so, we need to leverage technology to help a stagnant, number of providers to treat a growing pool of patients, without sacrificing the quality of care. And then finally, we've got environmental health. From air quality to water purity. It's important to understand the correlation between, the environment and the health care of our population. So, those are the pillars. I know I mentioned the HIGH FIVE, the fifth is not specific to healthcare. I touched on it a little bit earlier, but the fifth is, it is democratizing access to innovation, to resources, specifically for founders from underrepresented communities. >> And that's great insight, Michael great, great Schaeffer pointed that out. Manpreet take us on the final word here. Venture Capital, Startups, AWS, what's the current state share with us, the current worldview from your perspective. >> Oh, so, bringing home this point that MJ mentioned, the strategic plan of focus areas. And if you, look at all those strategic areas there's, you can really sort of put those into two buckets. One is the patient side of the bucket, and then there's the provider side of the bucket, or the caretaker side of the bucket. And if the patient side, what we want to do is work with startups that are, really working across a broad spectrum of use cases, but to solve those two key challenges of the, one on the patient's side and other on the provider side. Then the end goal of providing patient experience, and patient outcomes. For the patient side, it's the patient experience, patient engagement, patient outcomes. So, the startups looking on those sides, on those use cases of criteria. And then we have the provider side where, we want to ensure that the providers have the right set of technologies, the right set of solutions, right set of innovation, to help them where healthcare operations. You have all seen in COVID times, how the provider systems are getting overwhelmed. And that's where the healthcare operations comes into play. Clinical decision support. Now, many patients cannot get to the hospitals. So, how do we provide through our startup partners for startup customers, those solutions where remote diagnostics, remote imaging or remote health delivery could be provided. Things like predictive and prescriptive health solutions. How can we work with our startups to provide, those sort of solutions to the providers, to again, at the end, the better the outcome of the patients, right? So, that's what we were looking at. And that's what this program is all about. Working with public sector provider side of the house and the customers understanding, and helping them understand the need as well, and then bringing the right set of startup solutions, and help solve those challenges that they are facing, and the patients are facing as well. MJ, I'm sure you want to close it out, with some thoughts too. >> Okay. >> Absolutely, I would just close it with this, our goal, like Manpreet said, is to match the high potential startups, with the, the enterprises who are desiring those solutions, and success for us, we'll have three traits. It will be valuable, meaning that there will be a true alignment between what our startups offer and what the market needs. It will be measurable, so that we can quantify the improvement and outcomes. And finally, it will be sustainable. So, beyond COVID-19 beyond the opioid crisis, beyond any situation or condition, we look to bring solutions to market through our startups, that are going to truly sustain a transformative approach to modernizing public health enterprises. >> Great job again, and important work and DevOps, impacting healthcare in all kinds of ways. And it's super important work. I'm glad you guys are doing it, and it's going to develop out beautifully, and if I can give you a high five, Michael, I'll give you a high five off in-person, but remotely, >> Virtual. >> Get virtual high five great program. We're going to spread the word, good work. >> Thank you. >> Thanks for doing it, I appreciate it. >> Thank you very much for your time. >> Okay, it's theCUBE coverage virtual, we are theCUBE virtual bringing all the coverage, super important work being done in public sector, cloud enabling it, great people important, and of course, happening at re:Invent. Thanks for watching. (upbeat music)

(upbeat music) >> Announcer: From around the globe it's theCUBE. With digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS Worldwide Public Sector. >> Hello. Welcome back to theCUBE's virtual coverage of AWS re:Invent 2020 not only are we there in person this year we're remote because of the pandemic and all that going on with the virtual event three weeks coverage here and special coverage of public sector. Got a great guest, Lorraine Bassett, Chief of Staff in Public Sector of Sandy Carter at AWS. Thanks for joining us. >> Hey John and thank you very much for the invitation. It's really good to be here. >> We've had great conversations with Sandy Carter and her team at awards program really just last year. Just a lot of success stories now with public sector and the pandemic. There's been just a lot of things going on where the technology has pulled you know from the future to present and the public sector needs it the most. This is a key thing. What's your role there? How are you working with Sandy and the team? Take a minute to explain what your background is and your current role. >> So I recently joined the Sandy Carter's team as a Chief of Staff and business advisor. And originally just before then let up the, the go-to-market strategy for the internet of things and Smart Seas in the public sector. So bringing that experience and expertise into Sandy's team and really being able to help provide guidance and advise where necessary. I think that's... it's going to add value to the core team. >> John: Yeah. And certainly there's just been a massive demand. We've been reporting on it really since February just the surge of just the acceleration of digital-- >> Oh yeah. >> Transformation in public sector across the board from education to military agencies just amazing. A lot of things going on here >> Yes. At re:Invent. Can you tell me more about this new services inception go-to-market team because this is new. Take me through explain. >> Yeah it is new and it's really timely and, and a really pivotal new service that we're adding in and well of the new service team that we're creating. So it's really focused on partners. So you know with it's really has a core objective to develop strategy and execute plans for the rollout of new priority services and features across AWS's Public Sector partner teams. So really the new inception the new services inception team its goal is to really be the connection point and the feedback loop for partners with our AWS service teams, our service go-to-market teams and our worldwide public sector teams. We really want to make that transition and that cycle as easy as possible. Ultimately, the new services inception team's objective is really we're going to be able to deliver AWS services to public sector partners and our customers by building connections between all of our services, all our service launches, our public sector partners. And I think really pivotal to this is in all GEOS regardless of the size of the partners and the types. So you know let me just close that out to say you know our strategy it's focused on new services not either in private or if the services in Pre-GA you know that resonate more so in the public sector. And really our goal overall role is to identify you know monetization paths enable them as necessary building marketing and go-to-market assets and helping evangelize the service and increase adoption. >> The number one question is going to ask is why now? What's behind this motivation? Can you just add some commentary to why now is it the pandemic? Is it all things coming together as that cloud scale? I mean what's, what's (laughs) what's the motivation. Why now? >> Well, we you know AWS you know we release we have a lot of new services that yeah and our partners need to have visibility into these services early and yes you're right. There's also been a lot of change and new demand that we hadn't seen before with you know really just in 2020 has been really interesting on the types of different new news cases that we're seeing. So you know we have new services that we want to be able to bring to markets. And so you know and our public sector partners it's long been part of our AWS be the program. So that's nothing new. So what this team is aiming to do is really formalize that process and the program to ensure that we're really maximizing participation from public sector partners. You know how do we do this? So how do we do this differently? It's really ensure that partners are aware of new services that are coming down the road that could impact business or impact their business heavily. >> Yeah. >> And work closely with them to identify the joint value proposition develop go-to-market content and provide value. And you're right John, right? This is, it's all of the above but and it's really how we enable customers based on everything that we've learned and what they need for 20 you know as we go into 2021. >> Okay. So there's the million dollar question. I'm a partner, pretend I'm a partner, what's in it for me? I'm I making more money? Am I got to to go faster? >> Oh yeah. >> What's the benefits to me as a partner? >> So this is you know there, there are... So you're right. There are a lot of really good benefits. So there's a couple that come to mind straight away. So let's just, let's just pull out kind of really what's going to be important to the customers... To the partners first. Right firstly, so being part of a formal better program enables faster market which should lead to market differentiation on launch. So this early release and early visibility and early position is really critical I think to our partners. Secondly, there's an ability to influence roadmap early on through our feedback cycle. So all of our partners who work with us know that we're, we're all about innovation. We need to hear what is going on with our customers or with our partners and what we need to do to improve So you know that feedback cycle is key. And thirdly, you know Dedicate you know as you launch and go to market, you will have access to or partners have access to dedicated launch specialist team. That's assigned specifically to work with you on those, on those new services. And lastly, access to technical and sales expertise the sales expertise that will really help drive go-to-market motions. But you know I just... It is I think more than that and is there, there is an ability to diversify revenue streams. There is an ability to upsell and cross sell based on key learnings. And really as we, as we grow and learn from the new services we can build new business models through go joint go-to-market planning you know and really just take in some of the key benefits that the, the new services that inception team can offer. >> So what's the requirements to get in? All partners is there a pre-recs? Is that a wait list? Can you just give in kind of quick detail on how it works and how do people engage? How do the partners engage with the program? >> Now that's a good question. So really any APN tier partner consulting and technology partner that is really willing to commit to working with us is committed to testing developing public sector, partner and customer references and providing regular feedback. I mean really this is all about innovation. So we don't want to be specific and narrow on the partners who want to drive these or want to be able to drive these new services. >> What does a successful launch look like when you have your partners engaged, things are happening, the service new service team comes in. What's it look like take us through what success looks like here? >> Well success. So I think if you just kind of work backwards from this success you know it's really it's in our culture to be customer obsessed. So really success is it's key to listen to our partners and customers to help us build what that successful model would look like. So there's two questions we'd come up with is what services do we engage? And what partners should we engage? And that will help maximize our ability to be successful. So that what services we engage is, is linked to what resonates most for the public sector ecosystem. Now and the customers. So it also is looking at the most pressing challenges that customers are facing and also how the new service can help unlock value. >> Yeah. >> So that's success around the services. Now success around partners is you know what partners to engage that is you know that is around determining the ideal partner profile for example for service. And we do that by looking at competencies, references, vertical focus, and the customer base. And so you know going back to your original question about what is success it really is a strong alignment with partners and the services that really maximize the you know the strength of our go to market together. >> All right thanks so much for explaining the new services inception go-to-market team and capabilities. Final question where can people learn more information and get engaged? Can you share any data on, on what can they do? >> So the fastest path is to engage with the account team AWS and our partner development managers. Then you know there you can learn to and how to participate in future new service launches and facilitate introductions you know between us you know between the new inceptions teams so that we can get to know you. >> Lorraine Bassett Chief of Staff for AWS Public Sector partners. Great to have you on looking forward to hearing more of how it's going with Sandy. I know there's a lot of growth. A lot of action happening >> Yeah. >> With the pandemic public sector has an awakening. They've realized that now's the best time to pivot all those years of living in the antiquated old world is now coming to fruition. >> Yeah. >> Thank you. >> Yeah this is a very exciting time. Thank you very much John. >> Yeah. >> Really appreciated. >> It's going to be massive change and it's super exciting. Public sector is going to be moving very, very fast. >> Yes. >> Thanks for coming I appreciate it. >> Thank you. >> Okay so keeps coverage. I'm John Furrier. We are theCUBE virtual this year. We're not in person. This is part of AWS has been through all three weeks we've been here deep, doing deep dives, getting all the conversations. Thanks for watching. (upbeat music)

>> Instructor: From around the globe, it's theCUBE. With digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS Worldwide Public Sector. >> And welcome back to theCUBE's virtual coverage of AWS re:Invent 2020. I'm John Furrier your host. This is theCUBE virtual. Special coverage of the public sector. Today Rebecca Wetherly, Director of Worldwide Public Sector System Integrator Partners for AWS. Great to see you. Welcome to theCUBE virtual. >> Thanks, John. I'm glad to be here. >> So just the news we've been covering all through re:Invented priors, just the growth in public sector. The acceleration with the pandemic, it's just that this acceleration has been massive. So I want to just get get your take. It's been hard but also, it's been an opportunity for partners. >> You leading the Integrators. >> Sure. >> They're on the front lines. I got to ask you, (chuckling) what is AWS doing to support their partners, as the business models are forced really upon them to move faster? >> Yeah, sure. Thank you. Let me start with saying that, companies are really building a business in partnering with us. Because of global needs such as the pandemic. But we also have many partners that are coming to us because of our customer demand outside of COVID. Because we're a leader in cloud innovation, and because we've got a global field engagement and go-to-market strategy. You know AWS is a customer driven company, and our partners are also our customers. We have a full suite of programs for our partners and whether they be a consulting partner or a technology partner. We have tens of thousands of partners all across the globe, with more than 35,000 new partners since January 2016. And in our public sector space, we have over 1,500 partners with solutions and experience, delivering on a combination of government, education, and nonprofit customer missions all around the world. Consulting partners are really professional services firms. That help customers of all types and sizes design, architect, build, migrate and manage workloads and applications on AWS. They accelerate the journey to the cloud for our customers. And they often are implementing technology solutions. As you referred to around COVID, that our technology partners are actually developing. So consulting partners are SIs that I work with, Strategic Consultant Partners, Managed Service Providers, and also resellers. And they are providing really great value to our customers by providing strategic advisory services, implementation and migration services, Staffog. They also have great specialty depth and machine learning or AI. IOT, data lakes and analytics. And even in things like communication tools using technologies like we're doing today on zoom, and taking those to our customers. Our technology partners on the other hand they deliver hardware, connectivity services and software solutions that are hosted or integrated with AWS cloud. And they deliver components to broad customer solutions, often via our consulting partners. We have a great, a great way of delivering technology through our AWS Marketplace and we'll talk about that in a minute. But I will say, that our tech partners are helping our customers decrease their deployment times, provide cost optimization and infrastructure for DevOps and production workloads. They're also lowering their costs on code development by using our broad portfolio of services. And oftentimes for our public sector customers they are helping shorten the path to achieving regulatory requirements for our public sector needs. >> That's awesome. You guys have a lot to do there to support your partners. Obviously the main concern is, how do I maintain that profitability in the fast pace. And then making sure that their customers can also transition and ride the digital transformation wave. So I have to ask you, what programs are you guys offering to help these partners succeed because certainly it's beyond just the profitability. it's this new business model of Cloud-scale. So what programs specifically are you guys offering? >> Yeah, we have a lot of different programs at AWS. The first stop is really the AWS Partner Network. Which I'll refer to as the APN. This is really our global partner program for technology and consulting businesses to leverage Amazon Web Services to build solutions and services for customers. The APN is the first place where companies can build, market, and sell their offerings, and provide valuable business, technical, and opportunities for marketing with their customers. Our programs provide promotional support. We provide visibility throughout our website. We give partners opportunities to engage with customers for events, social media. And we provide access to funding and go-to market opportunities. I touched on briefly our AWS Marketplace . And this is really a great program offering to our customers both consulting partners and technology partners. The AWS Marketplace simplifies procurement and entitlement of provisioning software across 50 different categories. And we have more than 8,000 transactional listings. That marketplace connects customers with more than 1,000 different ISBs or independent software vendors to help meet their business needs. And we have more than 300,000 customers using software from the AWS Marketplace. The Marketplace is also available on 24 different regions. So when a customer chooses to use the Marketplace they have the opportunity to procure their software from our consulting partners and leverage the software and the technology from our from our tech partners. Other really cool programs we have are our Partner Transformation Program or SaaS Factory Program, and also our Migration Acceleration Program. >> Awesome. Great programs. What else are you guys besides programs, Are you guys doing >> Yeah. >> to help partners succeed. Because I know there's a lot of touches, there's some new things going on. What else do you guys do? >> Yeah, I think we have a lot of great resources available to our partners. Most of our partners have Partner Development Managers that are working with them on a daily basis. Access to our business development and sales teams, solutions architects and other subject matter experts. Really getting deep into the technology and having access to those folks to help our partners design, build, architect and validate a purchase with customers. Also our Professional Services Teams.Right? They are deep subject matter experts that our partners have the ability to tap into. And then of course, because of the way we go to market in public sector, access and engagement with our capture, bid, and proposal teams are super important. We also have to consider access for our partners to be trained and become certified. That's a real requirement that our customers need to help them achieve their goals. We offer digital and classroom training for our partners to be able to learn at their own pace or via an AWS instructor. And AWS training and certification helps our partners build competence, confidence, and credibility with our customers. We also have AWS competencies. And our competency program is designed to identify, validate, and promote APN partners that have demonstrated technical expertise and proven customer success. One of the most critical competencies for us is and these days is around our migration. Migration competencies allows our partners to accelerate their customer's cloud adoption journey by providing strategy, personnel tools, education, and tech support to their customers. One of those customers and partners is InterVision. They're a consulting firm that provide strategic advisory services to organizations to help them run, grow, and transform their business needs with the cloud via modern IT services. Their experts have a deep history in technology solutions and they have a deep bench of certified engineers and data scientists to excel delivering Managed Services and Migration Services to both public sector and commercial customers. And with the California Department of Technology. Which is a state agency that provides authority and responsibility over all aspects of technology for California state governments, they selected InterVision to work with them due to their expertise and their proprietary offering called Cloud Migration Lifecycle Assurance. And that offering provided that CDT, the ability, pardon me. To take advantage of their Cloud Migration operations and optimization specialty. So our partners are really getting great opportunities to build their business and to accelerate their their work with us through a variety of programs, and by really digging deep and leveraging all of the programs that are available to them. >> It's nice with the mix of programs, plus the field support, plus the care they're nurtured that, grow that. As you know in these in these markets where you have partnerships and channels and relationships. You need to be profitable. And profitability is about happy customers. >> Rebecca: Sure. >> And margins.(chuckles) Making money. >> Rebecca: Yeah. Sure. >> You got to make money to stay in business. So, this is a big opportunity as the new economics of cloud come into the channel. This is really a big conversation. Moving fast, scaling up, new kinds of services. The integrators are really having a good time here. And these are new practices. How can someone learn more? What's out there? How does someone get engaged with you guys? What information can they, is there a site? Is there a program? How does someone get the resources? What would they do? >> Yeah. Well, I will tell you. The first stop is really our website. And that may sound trivial but that is the best place to get started for us. You're going to find there by visiting https://aws.amazon.com. You can register to become an AWS partner very easily. Right there you're going to get step-by-step instructions and learning paths, as well as tutorials and how to get your business up and running, and how to become a partner. And the journey largely looks like this. Right? One. get on board. Get familiar. Establish your relationship and join the Amazon Partner Network. Go through some very basic training and get familiar with their services. Second. Develop those technical and sales skills. Develop a business model where AWS lends the greatest value to your partner business. And as you move through the tiers of maturity, we will co-invest in your business to help you scale. And then three, really go to market. Establish the pathways to your customers. Build out your differentiated approach. Look at the competencies we offer and decide which ones are going to be the most relevant to you. We want you to leverage the funding mechanisms we have, and we want you also to think about how we co-market together. There are so many roads to success and AWS offers lots of different partner programs and opportunities to develop your unique roadmap John. >> Yeah, that's great enablement. That is super valuable. Having the co-funding, the go marketing, and the tools and the programs. All there to enable services to be successful. Rebecca, thanks for sharing that program. >> My pleasure. >> Great to have you on. Rebecca Wetherly, >> Thank you so much. Director of the Worldwide Public Sector System Integrator Partners. A big growing part of the public sector when we need it the most, which is now and it's growing. So check them out. Thanks for watching. This is theCUBE coverage. CUBE virtual, for AWS re:Invent reinvent public sector, special coverage. Thanks for watching. (upbeat music)

>> From around the globe, it's theCube, with digital coverage of AWS re:Invent 2020. Special coverage sponsored by, AWS Worldwide Public Sector. >> Okay, welcome back to theCube's coverage, of re:Invent 2020 virtual. It's theCube virtual, I'm John Farrow your host, we're here celebrating, the special coverage of public sector with Sandy Carter, vice president of AWS Public Sector Partners. She heads up the partner group within Public Sector, now in multiple for about a year now. Right Sandy, or so? >> Right, you got it, John. >> About a year? Congratulations, welcome back to theCube, >> Thank you. >> for reason- >> Always a pleasure to be here and what an exciting re:Invent right? >> It's been exciting, we've got wall-to-wall coverage, multiple sets, a lot of actions, virtual it's three weeks, we're not in person we have to do it remote this year. So when real life comes back, we'll bring the Cube back. But I want to take a minute to step back, take a minute to explain your role for the folks that are new to theCube virtual and what you're doing over there at Public Sector. Take a moment to introduce yourself to the new viewers. >> Well, welcome. theCube is phenomenal, and of course we love our new virtual re:Invent as well, as John said, my name is Sandy Carter and I'm vice president with our public sector partners group. So what does that mean? That means I get to work with thousands of partners globally covering exciting verticals like, space and healthcare, education, state and local government, federal government, and more. And what I get to do is, to help our partners learn more about AWS so that they can help our customers really be successful in the marketplace. >> What has been the most, exciting thing for you in the job? >> Well, you know, I love, wow, I love everything about it, but I think one of the things I love the most, is how we in Public Sector, really make technology have a meaningful impact on the world. So John, I get to work with partners like Orbis which is a non-profit they're fighting preventable blindness. They're a partner of ours. They've got something called CyberSec AI which enables us to use machine learning over 20 different machine learning algorithms to detect common eye diseases in seconds. So, you know, that purpose for me is so important. We also work with a partner called Twist Inc it's hard to say, but it just does a phenomenal job with AWS IoT and helps make water pumps, smart pumps. So they are in 7,300 remote locations around the world helping us with clean water. So for me that's probably the most exciting and meaningful part of the job that I have today. >> And it's so impactful because you guys really knew Amazon's business model has always been about enablement from startups to now up and running Public Sector; entities, agencies, education, healthcare, again, and even in spaces, this IoT in space. But you've been on the 100 partner tour over a 100 days. What did you learn, what are you hearing from partners now? What's the messages that you're hearing? >> Well, first of all, it was so exciting. I had a 100 different partner meetings in a 100 days because John, just like you, I missed going around the world and meeting in person. So I said, well, if I can't meet in person I will do a virtual tour and I talked to partners, in 68 different countries. So a couple of things I heard, one is a lot of love for our map program and that's our migration acceleration program. We now have funding available for partners as they assess migration, we can mobilize it and as they migrate it. And you may or may not know, but we have over twice the number of migration competency partners doing business in Public Sector this year, than we did last year. The second thing we heard was that, partners really love our marketing programs. We had some really nice success this year showcasing value for our customers with cyber security. And I love that because security is so important. Andy Jassy always talks about how her customers really have that as priority zeros. So we were able to work with a couple of different areas that we were very proud at and I loved that the partners were too. We did some repeatable solutions with our consulting partners. And then I think the third big takeaway that I saw was just our partners love the AWS technology. I heard a lot about AI and ML. We offered this new program called The Rapid Adoption Assistance Program. It's going global in 2021, and so we help partners brainstorm and envision what they could do with it. And then of course, 5G. 5G is ushering in, kind of a new era of new demand. And we going to to do a PartnerCast on all about 5G for partners in the first quarter. >> Okay, I'm going to put you on the spot. What are the three most talked about programs that you heard? >> Oh, wow, let's see. The three most talked about programs that I heard about, the first one was, is something I'm really excited about. It's called a Think Big for Small Business. It really focuses in on diverse partner groups and types. What it does is it provides just a little bit of extra boost to our small and medium businesses to help them get some of the benefits of our AWS partner program. So companies like MFT they're based down in South Africa it's a husband and wife team that focus on that Black Economic Empowerment rating and they use the program to get some of the go to market capability. So that's number one. Let's see, you said three. Okay, so number two would be our ProServe ready pilot. This helps to accelerate our partner activation and enablement and provides partners a way to get badged on the ProServe best practices get trained up and does opportunity matching. And I think a lot of partners were kind of buzzing about that program and wanting to know more about it. And then ,last but not least, the one that I think of probably really has impact to time to compliance it's called ATO or Authority to Operate and what we do is we help our partners, both technology partners and consulting partners get support for compliance framework. So FedRAMP, of course, we have over 129 solutions right now that are FedRAMPed but we also added John, PCI for financial HIPPA for healthcare, for public safety, IRS 1075 for international GDPR and of course for defense, aisle four, five and six, and CMMC. That program is amazing because it cuts the time to market and have cuts across and have and really steps partners through all of our best practices. I think those are the top three. >> Yeah, I've been like a broken record for the folks that don't know all my interviews I've done with Public Sector over the years. The last one is interesting and I think that's a secret sauce that you guys have done, the compliance piece, being an entrepreneur and starting companies that first three steps in a cloud of dust momentum the flywheel to get going. It's always the hardest and getting the certification if you don't have the resources, it's time consuming. I think you guys really cracked the code on that. I really want to call that out 'cause that's I think really super valuable for the folks that pay attention to and of course sales enablement through the program. So great stuff. Now, given that's all cool, (hands claps) the question I have and I hear all the time is, okay, I'm involved I got a lot of pressure pandemic has forced me to rethink I don't have a lot of IT I don't have a big budget I always complaint but not anymore. Mandate is move fast, get built out, leverage the cloud. Okay, I want to get going. What's the best ways for me to grow with Public Sector? How do I do that if I'm a customer, I really want to... I won't say take a shortcut because there's probably no shortage. How do I throttle up? Quickly, what's your take on that? >> Well, John, first I want to give one star that came to us from a Twilio. They had interviewed a ton of companies and they found that there was more digital transformation since March since when the pandemic started to now than in the last five years. So that just blew me away. And I know all of our partners are looking to see how they can really grow based on that. So if you're a consulting partner, one of the things that we say to help you grow is we've already done some integrations and if you can take advantage of those that can speed up your time to market. So I know know this one, the VMware Cloud on AWS. what a powerful integration, it provides protection of skillsets to your customer, increases your time to market because now VMware, vSphere, VSAN is all on AWS. So it's the same user interface and it really helps to reduce costs. And there's another integration that I think really helps which is Amazon connect one of our fastest growing areas because it's a ML AI, breads solution to help with call centers. It's been integrated with Salesforce but the Service Cloud and the Sales Cloud. So how powerful is that this integrated customer workflow? So I think both of those are really interesting for our consulting partners. >> That's a great point. In fact, well, that's the big part of the story here at re:Invent. These three weeks has been the integration. Salesforce as you mentioned connect has been huge and partner- >> Huge >> so just just great success again, I've seen great momentum. People are seeing their jobs being saved, they're saving lives. People are pretty excited and it's certainly a lot of work you've done in healthcare and education two big areas of activity which is really hard corporation, really, really hard. So congratulations on that and great work. Great to see you, I going to ask you one final question. What's the big message for your customers watching as they prepare for 2021 real life is coming back vaccines on the horizon. We're hearing some good news a lot of great cloud help there. What's your message to send to 2021? >> 2021, for our partners for 2021, one, there is a tremendous growth ahead and tremendous value that our partners have added. And that's both on the mission side, which both Theresa and I discussed during our sessions as well as technology. So I think first messages is, there's lots of growth ahead and a lot of ways that we can add value. Second is, all of those programs and initiatives, there's so much help out there for partners. So look for how you could really accelerate using some of those areas on your customer journey as you're going along. And then finally, I just want John, everybody to know , that we love our partners and AWS is there to help you every step of the way. And if you need anything at all obviously reach out to your PDM or your account manager or you're always welcome to reach out to me. And my final message is just, thank you, through so many different things that have happened in 2020, our partners have come through amazingly with passion with value and just with persistence, never stopping. So thank you to all of our partners out there who've really added so much value to our customers. >> And Amazon is recognizing the leadership of partners in the work you're doing. Your leadership session was awesome for the folks who missed it, check it out on demand. Thank you very much, Sandy for coming on the sharing the update. >> Thank you, John, and great to see all your partners out there. >> Okay, this is theCube virtual covering AWS re:Invent 2020 virtual three weeks, wall-to-wall coverage. A lot of videos ,check out all the videos on demand the leadership sessions, theCube videos and of course the Public Sector video on demand. Micro-site with theCube. I'm John Furrier, thanks for watching. (upbeat music)

>>from around the >>globe. It's the Cube with digital coverage of AWS reinvent 2020 Special coverage sponsored by AWS Worldwide Public Sector >>Hi and welcome to the Q Virtual and our coverage of AWS reinvent 2020 with special coverage of the public sector. I'm your host, Rebecca >>Knight. >>Today we have two guests for our segment. We have Kevin McCallum Jr. He is the chief technology officer at Maximus. Thanks for joining us, Kevin, and we have way. And we have Steve Zimmerman, who is the vice president of consulting services at Insight. Thank you so much for coming on the show. Steve. >>Thank you for having us appreciate it. >>So I want to start by asking. You both have to tell us a little bit more about your company's. Kevin. Let's start with you. Tell us a little bit more about Maximus. >>Yes, Thanks for having me. Maximus is a 40 year old company. We partner with state, federal and local governments to provide communities with critical health and human service programs. We leverage extensive experience to develop high quality services and solutions that are cost effective and tailored to their unique needs. One of the things that we do is offer government's ability to programs rapidly and scalable so that we can focus on the automation and their operations. We do services from Medicare to Medicaid, Welford work, and we have comprehensive solutions. Help the government's run effectively and efficiently. >>Great, Steve, tell us a little bit about insight. >>Yeah, sure. Um, Insight is a Fortune 500 company, you know, in 2020 will roughly do you know, probably a plus billion dollars in revenue. Global company. You know, we have thousands of treaty GIC relationships, but I'd say we have probably a couple 100 partners. We focus on one of those key partners to us is a W s. Right. As we go to market, Azzawi start, you know, working with our customers around transformation, of which we're gonna talk a little bit about that today with Kevin as it relates, Thio incite public sector. It's >>a pretty sizable >>part of our business. You know, we'll do about $1.5 billion in revenue. We have 200 plus contract vehicles, will work out there over 500 plus teammates, and we're seeing that business grow quarter over quarter, 20% growth. So It's a big investment for us and really looking forward to hearing Kevin talk about Maximus, uh, to the team, because obviously it's a big lever for us for inside public sector to get the word out there about the great transformation work. What you do with our customers. >>That's a great segue. So let's go back to you, Kevin, and talk a little bit about Maximus. Cloud transformation. Why did you hire insight for help you with this? >>Yeah, A Z We started our journey. One of the things we realized is as we were moving to the cloud is the experience. We needed a trusted partner and we ran an RFP process looking for partners out there that have done it that have done major data center programs. You're moving large companies, you know, We're moving about 6000 workloads 160 plus applications. So it was not a light or easy project and insight fit that. Aziz, We went through the interview process. It became very clear that they have done this for Fortune 500 companies in the past and their experience is beneficial to helping us drive to the future and the other factors is we wanted to make sure that once we were done with the project, we had the experience internally that they helped us with Thio drive forward. >>So talking about the importance of a trusted partner, which is such a key component of digital transformation cloud journeys tell us a little bit about the the strategy tied to the data center transformation and why you chose AWS. >>Sure. So, as we started doing our research, we did analysis across all of the cloud providers who were out there. AWS is clear leader in the marketplace. Their technology is better aligned with what Maximus has as the underlying technologies were, ah, majority of Lennox Base. We also have windows. We have Oracle, which, with the AWS depth on breath of our offerings, tied better to what we had. The other thing we were looking to do is get rid of our monolithic off the shelf products and use mawr of the cloud based products that are out there. Amazon has a very deep, uh, native technology that allows you to replace your old services where you had to bolt on or purchase another product to something that is integrated and streamlined, you know, down Thio, how do you monitor your systems? How do you do logs things like that. And, you know, as we looked at the time frame, we had to deliver this. They had to be able to grow with us. So as we were building out, new infrastructure were able to build where previously internally. With data centers, you have to buy infrastructure. You wait for it to arrive, you install it. Amazon has it at the click of a ah button. So we're able Thio basically have environment stood up in a day rather than having to wait weeks for it. So and the last thing was up time. So you know Amazon. They're five nines plus in up time and most of our contracts or three nines or better requirements. We had to find a bender that had multiple availability zones and regions that allowed us to be flexible in how we deployed. >>So talking about the convenience and the ability to streamline, and also the need for flexibility in the covert era. Of course, the word hybrid work environments has taken on a new meaning. But I want to ask you about how you see the hybrid era in the long term affecting Maximus. >>Yeah. Since Maximus is a government contractor, we will always be in a hybrid, uh, set up. So some of our contracts are very restrictive, especially when you get into our S d. O. D. And some of those agencies you have a fed ramp requirement is right. Well, with some of the federal agencies. So some of those components about to stay internally So where we can force, uh, you know, moving to the cloud because of the flexibility we have to deploy, that is the right will go. Um, co vid has introduced a new complexity. When it started back in March, you know, Maximus had 30,000 or so employees, and we instantly were thrown into You gotta make those employees get those employees to work from home. So we used Amazon's workspace Thio push our employees to work from home, where, you know, some of the employees and some of our contracts are customer owned equipment. So we couldn't actually take that equipment home. So we had to move to a B y o d model on Amazon workspaces in order to get the users to work from home and the complexity that, with what Amazon has to offer, allowed us to quickly move over 25,000 employees on the Amazon workspaces and work from home and then keeping the data center migration moving in the middle of it has also been, ah, challenge. So we will, in our federal space, still have internal data centers. Integration points that Amazon offers with their inter connects is key toe. How we make it a seamless process because we may have a business unit has stuff sitting in the data center and at Amazon, and they have to look at the seamless package. >>Steve, I want to bring you in here a little bit into this conversation. Cloud transformation, digital transformation. These are These are difficult and huge undertaking in the best of times. How does this pandemic this health crisis emergency. How has that affected the way you help your clients the way you work with your clients? Collaborate, communicate, talk a little bit about the effect of Kobe on this on the >>eso I would. I'll answer the question in a couple different ways, so I would agree with Kevin because, you know, forget about what we do with our customers. You know, we had a pivot really quick to write all remote workforce. You know, I think about my team, you know, 1000 plus teammates. Everyone's 80% travel all gone like, um, and I write eso everybody working remote. Everybody work from their homes. And but the challenging part was working with our customers. And, you know, I look at you know, I looked at with Kevin. You know, I've never met Kevin in person, you know, frankly, and there's teammates have come on to our to the project and execute executing this program remotely, so it makes it that much harder working with the customer. Um, you know, doing more video chats. You know, our methodology is built to be all remote. We have a proprietary tool called snap start that allows to bail scan environments. All that things done. Remote migrations could be done remote. The hard part is when you have to go on site because there's this stuff you have to go on site for around physical inventory to look at the equipment, but it just makes it that much harder. You know, I think he taking advantage of these video tools like we're doing today. You know, I can't tell me how many Skype You know how many calls have been on with Kevin like this and with his peers and with his leadership. But communication is really important program like this because, you know, in a program like this, there will be problems, right? And there will be challenges and, you know, getting on a call on being I will look at Kevin face to face and see what his reaction is really key. But you gotta work that much harder. You gotta work that much harder now in the pandemic. You know, I have other projects right now leaving with this other projects that, frankly, we have sold all remote and we're doing it all remote. And what I'm seeing with the bidam IQ is an acceleration of digital transformation. So, other similar projects like we're doing with Kevin. We're doing for other large fortune 500 companies because it's an acceleration of Hey, look, we gotta be old digital now, so it'll be interesting to see you know how the pandemic effects is long term because it is definitely accelerating out their digital transformation if you haven't done it, you're in trouble because it's gonna eat your company alive. >>Mhm. So, Kevin, he's talking. He talked a little bit about she talked a little bit about the importance of communication, particularly when work so many people are working from home. Um, talk a little bit of about other best practices that have emerged. Things that you have noticed. Things that you advice you would have to your peers. I mean, a Z we heard from Steve. If you're not there yet, you're in trouble. But for the for the people, for the executives out there who are watching this, What advice would you have for them? >>Yeah, I think that you know this this is brought to light. You know, there was always a view that you had to be in an office on a white board and actual actually functioning in that fashion. So, you know, before the pandemic, I was traveling three weeks a month on now, not traveling. I feel that I actually get more work done. I actually feel that I'm closer to the team just because we've introduced a lot of different digital channels. So now we have slack we have teams we do zoom. I require everybody to be on a on video, whereas previously before the pandemic you'd rarely have anybody on video. Um, and you've seen Ah, transformation is people pick up the phone a lot quicker than they did in the past. So it is, actually, I believe, brought the team closer together because now you know, everybody's on. Um, the downside of it is everybody's on all the time. So you've also had to have people step away from work because generally when they take PTO, they leave the office that go somewhere with their family. Now it's your kind of at home. There's not much to dio. You kinda have to force them to take the time off. One of the major factors that has has been interesting is we're doing this transformation in the middle of co vid with moving. All of our resource is the home. So we've we've had to take pauses, toe focus on getting everybody to work from home. Okay, now their work from home back to the project. And, you know, it's kind of a change the timeline a little bit, but in the end, you know we have some hard deadlines to meet. So it's been an interesting transition. You >>know, Kevin, um, I wanna agree with you two points is, uh you know, I think we're also getting not only your time, but also senior leadership, that I think, frankly, we never would have gotten, you know, I'm talking, you know, your peers and your leadership, Like I would fly for those meetings. I think about all the time that I've saved. But then again, it never ends, right? Never. It begins and never ends. And, you know, one of the things I'm concerned about is you know, the long term burnout factor for these folks because and depending on what state you're in, it never ends. You don't have anywhere to go, right. And you know, I think about teammates. I think you know, Kevin, I have talked about this related to our project like burdens and really thing right now for sure. 889 months into this thing. It's a real thing. Is people they have to focus on. Is is work sometimes. So it's a it's a concern for all of us is a project team is we start looking at the executing. This continue to execute this program for the next year. >>And it really highlights the importance of visionary leadership and a leader who cares who is empathetic, who is checking in with his or her team and making sure that the colleagues feel appreciated and cared for. I want you both to just give us look into your crystal ball is a little bit and talk about the where you see things 12, 24 months from now. Hopefully there will be a vaccine and we will return to somewhat of a of a new normal. Um, talk a little bit about where you see the Maximus transformation in two years. Absolutely. Yeah. Start with you. >>So s so you know, our cloud migration. We have some hard deadlines through next year, so we have a focus with insight to get that completed by September next year because our data center contracts are up and we've got to get out. You know, one of the the advantages of where we're headed is to move into more of a Dev ops model where you know you're able thio enable groups that have previously not been able to do work just do thio. The infrastructure was set up your now, enabling them to do deployments, get into production and have full stack ownership. That's really where our focus is. Is enablement of the teams that couldn't do the work previously because now you're in a different type of environment. Um, the other thing is being able thio be more agile. So as we move forward into the cloud journey, we as a company are consort contracts quicker. We are part of the, you know, contract tracing on unemployment insurance. We've done a lot of contracts with states that you know previously most of our contracts or anywhere from a 62 120 day startup. These contracts and contact tracing and covert projects. We've had to start them up in three days. That's having 500 employees online on workspaces on Genesis Cloud and fully functional, and it has been a challenge. But it also has introduced a a better way to do business because now we can we can move quicker for our customers and we can get contracts where they come and say, Hey, I need something in the next couple days. If you look further down the road. You know, it's taking the advantage of what Amazon has to offer, you know, moving from arm or monolithic programs like, you know, we sit on Oracle on Lenox today. You know, we could move into Aurora, which opens up the doors and floodgates, because then you manage, er a little differently. You manage your data a little differently. That's really where I think the the market's going and where we can actually transform our business. Even better, Thio, where we could be more flexible. We can start up quicker and, you know, be doom or things for our customers. >>The final word from you >>e I think it's gonna be a hybrid world, right? It's at least in the short term. And you know, we believe it's all about the workload and getting those workloads or applications, you know, in in the right spot, whether it be public or private and helping our customers with that journey, you know, just a pile on with Kevin talked about around Dev ops. Once you get a guy to get once you get all the stuff over there, you still got to manage it, Whether it's in a W. S or, you know, on Prem. You still gotta have a process to do that. So we see a lot of opportunity around the Modern I t operations and helping with that way. We want to continue to be a trusted partner. Thio Maximus. It's been a great relationship, but I want to thank Kevin and his his leadership team for trusting in us. And we look forward, Um, or more success with him in the future. >>Excellent. Thank you both so much. Kevin and Steve, thanks so much for coming on the Cube. >>Absolutely. Thank you. >>I'm your host, Rebecca. Night. Stay tuned. For more of the Cube virtual coverage of AWS reinvent with special coverage of the public sector.

>> Announcer: From around the globe. It's theCube with digital coverage of AWS re:Invent 2020 special coverage sponsored by AWS Worldwide Public Sector. >> Hi, and welcome to theCube Virtual in our coverage of AWS re:Invent. I'm your host Rebecca Knight. Today we are joined by Shawn Snyder. She is the managing director at Deloitte and Cloud Migration market leader. Thanks for coming on the show Shawn. >> Thank you, Rebecca. I'm glad to be here. >> So we're talking today about cloud migration in the public sector in the COVID era, but I want to start by having you introduce yourself to our viewers tell them a little bit about what you do at Deloitte. >> Sure, I'm Shawn Snyder. I'm a managing director based out of Atlanta. I lead our cloud migration offering for our government and public sector clients. So that really means that I serve clients in the government, both public sector local government agencies, as well as federal agencies and helping them move to the cloud, and I'm also responsible for building out our capabilities, our tools, our resources, and people to help clients do that in a very fast and accelerated way. >> So even putting aside the pandemic for a second, shifting to the cloud is such a big and daunting undertaking for so many organizations, including federal agencies. How do you help CIOs and clients think through the processes and what they need to do and how they need to do it? >> Yeah, I mean, it all starts with where are they at on this journey, right? We actually have a show our clients like a typical journey to the cloud and, you know, we have a method and set of tools that we can work with them depending on where they are but if they're just in the initial stages of exploring, moving to cloud, it typically starts with a strategy and really understanding what, you know, how engaged is the mission and the agencies in supporting this. Are they really looking to continue to build their own talent? What is the end state look like? Do they want to build cloud skills and cloud engineering skills within their organization, or are they looking to do more of a managed service model? So a lot of these conversations happen and also around what platforms they want to use and then we typically look at their portfolio of applications. So it could be, you know, they're looking to move out of a data center and go more to a cloud virtual environment. It could be that they're looking to move a couple of mission critical applications that are highly complex with lots of data and sensitive information, so. It really kind of depends on what they're trying to achieve and what is the business result that they're looking to gain. >> And how do you help them think through the business case for this? Because I know that that is definitely an imperative. >> So we take a couple of, I can give you an example. So when we were working with a state in local agency, looking at a big mission critical integrated eligibility system, they wanted to be able to move because they were, the technology was getting a little dated. It was eating inflexible to maintain and when they were looking at the maintenance costs that they were spending on both the infrastructure and the application, it was starting to, you know, take up to 90% of the budget and so the lack of ability to be able to do new capabilities and new innovation when you're talking about especially post COVID, which I know we haven't gotten into, but when they're looking, there's actually more and more products and aid that's being made available. So they need more flexibility, and so what we did was we actually did a bunch of analysis around what does that technology stack look like? What's the cost drivers and then we built out what the future would look like on the, in this particular case was the AWS platform. How could they take advantage of some native services and reduce some of their licensing costs? How could they upgrade through our products? We have a seamless way to upgrade to cloud suitable operating systems. So in this case, they were on an outdated Windows and Linux platforms. We were able to update that to cloud suitable, which allowed them to, you know, save a lot of money in terms of their infrastructure costs to maintain some of that outdated infrastructure and then we get them on end state tools around security monitoring, around infrastructure monitoring and so they can really streamline some of those infrastructure costs as they are spending tremendous amount of money just on the tools when they're managing all of that on-prem, on a complex system. >> So thinking about now we are in this pandemic, which has changed everything about the way we live and the way we work, moving to the cloud was a business goal. Something that a lot of organizations sort of had, in they're two and three year, two and five-year plan. Now it is an absolute mandate. What are you seeing? What are you hearing? What are organizations saying to you now? >> There's just such a, there's such a demand for speed and doing it at scale very fast. So prior to COVID, like you said, it was a multi-year journey. We'll get to it when we can, but there were other priorities that automatic, always got in the way of that and also just the cost justification, right? When you're talking about migration and a lot of times these systems that's portfolio systems are outdated, they're not cloud suitable. So how do you have to refactor them? That can get pretty costly pretty quickly. Now our clients want to move fast and they have a virtual work workforce, they need more scale. They need more storage for some of the data. They need to be able to integrate with other partners, especially in the healthcare space, whether it's at the state and local agency level or in the federal space, that ability to create that ecosystem of being able to transmit and share data in a very secure way at a very large volume is becoming, you know, mission critical with combating COVID with being able to protect our citizens. >> Speed is the name of the game, as you're saying. So what, how is Deloitte investing in automation and what kinds of migration accelerators are you bringing to clients now? >> So a few different things. One, we are partnering with AWS, both on a professional services perspective, as well as with some programs. So we've integrated our methodologies and we've been certified by AWS for our methodology around migration acceleration program. So that's the map because of our qualifications of the amount of migrations we do globally, as well as our methodology and tool set, we're able to offer this joint map program, which allows us to team with AWS. Go on site in quickly use our tools to diagnose what applications are actually at cloud ready to move, how fast can they move? And it gives a lot of information around technical configurations, what servers they reside on, and all of basically the affinities, all of the information you would need to be able to move those applications and if it's not cloud suitable, we can detect if it, how quickly we could get it cloud suitable. What would need to be done is an application code, or is it database, or is it operating system? What are those things that need to get upgraded to move it to the cloud? And is it worth moving to the cloud? So we actually look at the business value that each of these applications are providing and saying, you know, this might be more suited to stay on-prem for now. So we work with them through this map program to really come up with that detailed migration schedule and plan and we then use that information that we collected during that diagnostic phase feeds into our migration tools. So the migration is actually automated with the information that was collected during the diagnostics and the landing zones, and all of the sizing of the infrastructures able to be sized appropriately based on the information that was collected. >> I want to ask you about innovation. In a lot of these Cube Virtual conversations that we're having, we're hearing from a lot of executives that the pandemic has been a forcing mechanism in sort of forcing people to think more resourcefully, more ingenuitively about how they solve these pressing problems. What have you experienced, and have you seen in particular examples of innovation that have been inspiring and exciting for you? >> Yes, absolutely. So I actually work in the federal health space most, and our ability to be able to stand up an application or a service, whether it's a Salesforce service, the AWS platform, but we've been able to stand up contact tracing for local agencies, for state agencies. We've been able to set up cloud native services that allow the data that's getting collected across these different organizations to be able to make meaningful information using machine learning and some of the other native services that are available within cloud and they can be stood up very quickly and very cost-effectively and I think that's the other value that cloud is unlocking for organizations and really now starting to realize that they can move towards innovation and start to spend much more money on innovation than what they were doing previously on spending most of the budget on maintenance. >> When you're talking to clients now about the future, what are they thinking? What's on their minds in this sort of this 12 to 24 month plan? Are they just thinking we just need to get through this next period and cope with this uncertainty? Or are they thinking about the future. >> Moving to cloud isn't just an infrastructure move. I think that's getting your head around what does it mean? What does your workforce have to look like? What does, how do you collaborate with the business? What are the, what is the future innovation use cases? What is going to, how do you actually start to use those use cases to demonstrate early value and start to do things much more in an agile and iterative way instead of, you know, delivering something in a, you know, several months or years. So it, it really is shifting, it's a transformation for how the office of the CIO or how they actually operate. It's creating integrated teams within the CIO organization. We're actually embedding different disciplines like engineering, infrastructure, IT operations, security operations, risk management, financial management, these disciplines as part of these, what we call DevOps DevSecOps type teams, and be able to deliver an end-to-end product on a particular platform in a very agile way. >> In thinking about the future of the workforce and how the pandemic is changing people's careers. I know that you serve as the technology campus champion at Georgia Tech, and you're very active in recruiting bright young business talent. Can you talk to our viewers a little bit about the changes that you foresee in terms of how people plan their careers and their professional development and anything in particular that Deloitte is doing to make sure that the pandemic does not have such a damaging effect, you know, from a lot of statistics that women are dropping out of the workforce in large numbers. >> Yes, so let me unpack your question a couple of ways. So, you know, first of all, you know, I'm really passionate about talent development and recruiting, and I've learned recruiting efforts at the undergrad for many, many years, and I've always been a technologist. So now, like just seeing how technology is embedded in all of the business that we do and it's so mission critical, you now, I'm very focused on making sure there's more women and more minorities going into technology oriented degrees. There's so much you can do with a technology degree and the of career careers that are available, you know, are unlimited. We can't hire enough people that have the right skills. There's just a war on talent for people that have the right security and cybersecurity skills, cloud engineering skills, and just the analytical skills. I mean, this is very complex stuff that you're trying to, you know, build stuff and create stuff that hasn't been created before. So I find it extremely fascinating and I hope that people can see the creative side of things and the scientific it's really bringing it both together and that's what I try to mentor a lot of the recruits on campus. In addition to that, so I think that there's tremendous amount of opportunity for folks going into those types of degrees, as well as for women I, you know, it's been a challenge because people are, you know, some schools aren't closed are not open. If you have a dual working family, it can be a big challenge if you're taking care of children or elderly parents, for example. So at Deloitte, we actually recently implemented a dependent care policy for folks that could take advantage of additional stipend to subsidize, you know, childcare or dependent care. So that's helped a little bit, we're also really focused on diversity inclusion. So, you know, really having candid conversations, individual conversations around what are your boundaries at work right now? Can, do you have to be off right now from, you know, dinner time till bedtime? What does that look like? And we're trying to really help people have the tools and feel comfortable about having those conversations, 'cause it's not just women, it's men, too. I mean, this, these are difficult situations that we're all, you know, co living with our spouses and our significant others and our children, and potentially, you know, extended family members and trying to work in the same environment and is very challenging, and so we're trying to create space for people to be able to have those conversations and make it work for them. >> Don't I know it's Shawn. So just in terms of thinking about the future and what is next for Deloitte, and you've just talked about how you are a technologist at heart, and you see so much excitement about bringing in different disciplines, different functions to solve these urgent and pressing problems. What do you foresee for yourself and for Deloitte over these next couple of years, as we emerge hopefully out of this crisis situation. >> I think Deloitte, you know, one reason I've stayed at Deloitte for so long is that we've always been really focused on how does the technology solve the business problem, the mission problem? And so we have a real opportunity to continue to be able to bring the IT and the technology enablement and make sure it aligns to the business strategy and so the business use cases, you know, we've invested a lot in our labs Capabilities where we're able to bring different disciplines, whether it's, you know, HR and talent thinking about workforce of the future, you know, that technology stack and the architects together, as well as the thinking about across the ecosystem, what are some of the future use cases that you're not even thinking about? So we're able to bring a lot of these different disciplines or subject matter experts together. Now I'll be in a very virtual way, but we've been able to take these lab concepts and it really helps kind of get that out of the possible defined and really strong alignment across these different constituents across the enterprise. So that is really exciting to me. I also think the investment that we're making in our cloud engineering practice, in our alliances with companies like AWS, it really gives us insight into where the technology is going and making sure our staff and our tools and our resources available to us are aligned to that more than investments are being made in the technology. >> So well Shawn thank you so much for coming on theCube Virtual. It's a pleasure having you on the show. >> Thank you very much Rebecca. >> I'm Rebecca Knight stay tuned for more of theCube Virtual's coverage of AWS re:Invent 2020.

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020. Special coverage sponsored by AWS Worldwide Public sector. >>Welcome to the Cube. Virtual. This is our coverage of aws reinvent 2020. Specialized programming for worldwide public sector. I'm Lisa Martin. Got a couple of guests here from No. Veta, please welcome Steven Adelman, principal computer scientists, and Kevin Healed, vice president of Information Exploitation. Gentlemen, welcome to the Cube. >>Thank you. >>Thank you for having us. >>Alright, guys. So? So, Kevin, we're going to start with you. Give our audience an introduction to Nevada. What do you What do you guys do? Who are you? How do you play in the public sector Government space, >>right? Yeah. Thank you, Lisa. Eso, Nevada Nevada is a technology services company focused on government solutions. So primarily national security solutions. Eso think customers such as Doody, the intelligence community, FBI, law enforcement and things like that about 13 1300 employees worldwide, primarily in our in our field. Clear resource is, um, that really focused on cloud for solutions for our customers. So solving the tough mission challenges our customers have, so that could be in technology solutions such as Data Analytics A I M L i O T. Secure Workloads, full spectrum cyber Cobb video processing. Really anything that's a high end technology solution or something we do for the government. We have been a privilege. We have. It's a privilege to be a partner with AWS for for some time now. In fact, I think the first reinvent we may have been to Stephen was six years ago. Five years ago, two >>1012 or 13 >>s So we've we've we've been around for a while, really kind of enjoying it and certainly sad that we're missing an in person reinvent this year, but looking forward to doing it virtually so, we're actually advanced your partner with AWS with a machine learning and government competency. Andi really kind of thio pump the m l side of that. That was one of our first companies with compasses with AWS and led by a center of excellence that I have in my division that really focuses on machine learning and how we applied for the Michigan. And so, um, really, we focus on protecting the nation and protecting our activities in the country >>and on behalf of the country. We thank you, Steven. Give me a little bit of information from a double click perspective as computer scientists. What are some of the key challenges that no, that helps its customers to solve. And how do you do that with a W s? >>Yeah, Thank you. So really as, ah, company, that is is data first. So our initial love and and still are kind of strongest competency is in applying solutions to large data sets. And as you can imagine, uh, the bigger the data set them or compute you need the the more resource is you need and the flexibility from those resource is is truly important, which led us very early, as especially in the government space and public sector space to be in early. A doctor of cloud resource is because of the fact that, you know, rather than standing up a 200 node cluster at at many millions of dollars, we could we could spend up a W s resource is process a big data set, and then and then get the answers an analyst or on operator needed and then spin down. Those resource is when When when that kind of compute wasn't needed. And that is really, uh, kind of informed how we do our work Azaz Nevadans that that cloud infrastructure and now pushing into the edge compute space. Still kind of keeping those cloud best practices in play to get access to more data. That the two, the two biggest, I think revolutions that we've seen with regards to using data to inform business processes and missions has been that that cloud resource that allows us to do so much with so less and so much more flexibly and then the idea of cheap compute making it to the edge and the ability to apply sensors thio places where you know it would been a would have been, you know, operational cost prohibitive to do that and then, ironically, those air to things that aren't necessarily data analytics or machine learning focused but man, did they make it easier to collect that data and process that data and then get the answers back out. So that really has has has kind of, uh, shaped a lot of the way Nevada has grown as a company and how we serve our customers. >>So coming back over to you lets. One of the things that we've been talking about almost all year is just the acceleration in digital transformation and how much faster organizations, private sector, public sector need to innovate to stay relevant, to stay competitive. How do you are you working with government customers to help them innovate so quickly? >>You know, we're very fortunate that a set of customers that focuses actually innovation it's focuses. I rad on. Do you know we can't do the cool things we do without those customer relationships that really encourage us to, um, to try new things out and, quite frankly, fail quickly when we need Thio. And so, by establishing that relationship, what we've been able to do is to blend agile development. Actual acquisition with government requirements process, right? If if you know the typical stereotype of government work is it's this very stovepiped hard core acquisition process, right? And so we have been fortunate to instead try quick win kind of projects. And so one of the biggest things we do is partner with our government customers and try to find it difficult, um, challenged to solve over 6 to 12 month time, right? So instead of making this long four or five year acquisition cycles like show me, right. How can we solve this problem? And then we partner with the mission partner show success in six months show that we can do it with a smaller part of money, and then as we're able to actually make that happen, it expands in something bigger, broader, and then we kind of bringing together a coalition of the willing, if you will in the government and saying, Okay, are there other stakeholders to care about this problem, bring them on, bring their problems and bringing together? You know, we can't do that with some of the passionate people we have, like Stevens. A perfect example. When we talk about a car in the projects we're doing here, Stevens passion for this technology partner with our customers having these challenges and try to enhance what they're doing is a powerful combination. And then the last thing that we're able to is a company is we actually spend a decent amount of our own dollar dollars on I rad S O. R and D that we fund ourselves. And so, while finding those problems and spending government dollars in doing that. We also have spent our own dollars on machine learning Coyote sensor next Gen five g and things like that and how those compartment together partner together to go back to the government. >>Yeah, yeah, So I would even say, You know, there's this. There's a conventional wisdom that government is slow in plotting and a little bit behind commercial best practices. But there are There are pockets in growing pockets across the government, Um, where they're really they're really jumping ahead of, ah, lot of processes and getting in front of this curve and actually are quite innovative. And and because they kind of started off from behind, they could jump over a lot of kind of middle ground legacy technologies. And they're really innovating. As Kevin said with With With the card platform, we're partnering with um P E O Digital in the Air Force in South C, D. M and Air Force security forces as that kind of trifecta of stakeholders who all want toe kind of saw a mission problem and wanted to move forward quickly and leave the legacy behind and and really take a quantum leap forward. And if anything, they're they're driving us Thio, Innovate Mawr Thio Introduce more of those kind of modern back practices on bond. Nevada as a company loves to find those spots in the government sector where we've got those great partners who love what we're doing. And it's this great feedback loop where, um, where we can solve hard technical problems but then see them deployed to some really important and really cool and impactful missions. And we tend to recruit that that set that kind of nexus of people who want to both solve a really difficult problem but want to see it executed in a really impactful way as well. I mean, that really grates a great bond for us, and and I'm really excited to say that that a lot of the government it is really taking a move forward in this this this realm. And I think it's it's just good for our country and good for the missions that they support. >>Absolutely. And it's also surprising because, as you both said, you know, there is this expectation that government processes or lengthy, you know, laborious, um, not able to be turned around quickly. But as Kevin, you just said, you know helping customers. Government agencies get impact within 6 to 12 months versus 4 to 5 years. So you talked about Picard? Interesting name. Kevin. Tell me a little bit more about that technology and what it is that you guys deliver. That's unique. >>Well, honestly, it's probably best to start with Stephen. I can give you the high level. This is Stevens vision. I have to give him credit for that. And I will say way have lots of fun. Acronym. So it isn't Actually, it isn't backward. Um, right. Stephen doesn't actually stand for something. >>It stands for Platform for Integrated, a C three and Responsive for defense on >>Guy. You know >>that the Star Trek theme is the leg up from the last set of programs I had, >>which were >>my little ponies. So >>Oh, wow. That's a definite stuff in a different direction. Like >>it? Part of the great thing about working in the government is you get to name things, cool things, so but t get to your question eso So Picard really sprung out of this idea that I had a few years ago that the world but for our spaces, the Department of defense and the federal government was going to see a massive influx of the desire to consume sensors from from areas of responsibility, from installations and, frankly, from battlefields. Um, but they were gonna have to do it. In a way, um, uh, that presented some real challenges that you couldn't just kind of throw compute editor, throw traditional I t processes at it. You know, we have legacy sensors that are 40 years old sitting on installations. You know, old program, a logical controllers or facilities control systems that were written in cobalt in the seventies, right in the world are not even I, p based, most of them bond. Then on the other end of the spectrum, you have seven figure sensors that air, you know, throwing out megabits of second of data that are mounted to the back of jeeps. Right, That that air bouncing through the desert today. But we'll be bouncing through the jungle tomorrow, and you have to find all of those kind of in combined all of those together, um, and kind of create a cohesive data center for data set set for you know, the mission for, um, you know what we call a user to find common operating picture for a person. Thio kind of combine all of those different resource is and make it work for them. And so we found a great partner with security forces. Um, they realized that they wanted Thio to make a quantum leap forward. They had this idea that the next defender So there are there, like a military police outfit that the next defender was going to be a data driven defender and they were gonna have to win the information war war as much as they had to kind of dominate physical space. And they immediately got what we were trying to achieve, and it was just just great synergy. And then we've piled on some other elements, and we're really moving that platform forward to to kind of take every little bit of information we can get from the areas of responsibility and get it into a you know, your modern Data Lake, where they can extract information from all that data. >>Kevin, as the VP of information exploitation, that's a very interesting title. How are you helping government organizations to win the war on information? Leverage that information to make a big impact fast. >>Yeah. I mean, I think a lot of it is is that we try to break down the barriers between systems on data so that we can actually enable that data to fuse together to find and get insights into it. You know, as ML and I have become trendy topics, you know, they're very data hungry operations. And I think what Steven has done with the card and his team is really we want to be able to make those sensors seamless from a plug and play perspective that Aiken plug in a new sensor. It's a standards based, uh, interface that sends that data back so that we can and take it back to the user to find Operation Picture and make some decisions based off of that data. Um, you know, what's more is that data could even refused with more than the data that Stevens collecting off the sensors. It could be commercial data, other government data and I think is Davis. As Stephen said earlier, you have to get it back. And as long as you've gotten back in Labour's share with some of our mission partners, then you can do amazing things with it. And, you know, Stephen, I know you have some pretty cool ideas and what we're gonna do on the edge, right? How do we do some of this work of the edge where a sensor doesn't allow us to pull out that data back? >>Yeah, and and Thio follow on to what you were kind of referring to with regards to thio handling heterogeneous data from different sensors. Um, one of the main things that our government customers and we have seen is that there are a lot of historically there are a lot of vertical solutions where you know, the sensor, the platform, and then the data Laker kind of all part of this proprietary stack. And we quickly realized that that just doesn't work. And so one of the major thrust of that card platform was to make sure that we had ah, platform by which we could consume data through adapters from essentially any sensor speaking. Any protocol with any style data object, Whether that was an industry standard or a proprietary protocol, we could quickly interested and bring it into our Data lake. And then to pile on to what Kevin was talking about with compute. Right? So you have, uh, like, almost like a mass locks hierarchy of needs when it comes to cyber data or thio this coyote data or kind of unified data, Um, you know, you wanna turn it into basic information, alerts alarms, then you want to do reporting on it, or analytics or some some higher level workflow function. And then finally, you probably want to perform some analytics or some trending or sort of anomaly detection on it. And and that gets more computational e intensive each step of the way. And so you gotta You gotta build a platform that allows you to to both take some of that high level compute down to the edge, but also then bring some of that data up into the clouds where you could do that processing, and you have to have kind of fun jubilate e between that and so that hard platform allows you to kind of bring GP use and high processing units down to the edge and and make that work. Um, but then also and then as maybe even a first passive to rule out some of the most you know, some of the boring gated in the video Analytics platform. We call it Blue Sky and Blue Ocean. Right, so you're recording lots of video. That's not that interesting. How do you filter that out? So you're only sending the information The interesting video up eso You're not wasting bandwidth on stuff that just doesn't matter on DSO. It's It's a lot of kind of tuning these knobs and having a flexible enough platform that you could bring Compute down when you need it. And you could bring data up to compute on Big Cloud while you need it, and just kind of finding a way to tune that that that really does. I mean it. You know, that's a lot of words about how you do that. But what that comes to is flexible hardware and being able to apply those dev ops and C I. C D platform characteristics to that edge hardware and having a unified platform that allows you to kind of orchestrate your applications in your services all the way up and down your stack, from micro controllers to a big cloud instant creation. >>You make it sound so easy. Steven Kevin. Let's wrap it up with you in terms of like making impacts and going forward. We know the edge has exploded, even mawr, during this very interesting year. And that's going to be something that's probably going to stay, um, stay as a permanent impact or effect. What are some of the things that we can expect in 2021 in terms of how you're able to help government organizations capitalize on that, find things faster, make impact faster? >>Yeah. I mean, I think the cool thing we're seeing is that there's a lot more commoditization of sensors. There's a lot more censored information. And so let's use lighters. Example. We you know, things were getting cheaper, and so we can all of a sudden doom or or more things at the edge, and we ever would have expected. Right when you know Steven's team is integrating camera data and fence data from 40 years ago, you know, it's just saying on off it's not do anything fancy. But now we you know, you know, Stephen, I camera whether Metro you gave him before was, but the cost of light are has dropped so significantly that we can now then deploy that we can actually roll it out there and not being locked in their proprietary, uh, system. Um, so I see that being very powerful, you know? Also, I can see where you start having sensors interact with each other, right? So one sensor finds one thing and then a good example that we've started thio experiment with. And I think Steve, you could touch on it is using triggering a sensor, triggers a drone to actually investigate what's going on and then therefore, hybrid video back and then automatically can investigate instead of having to deploy a defender to actually see what happened at that. At that end, Points dio e don't know. There's it's amore detail you can provide there. >>Yeah, No. So exactly that Kevin. So So the power of the sensor is is something something old that that gives you very uninteresting Data like a one or a zero on on or off can detect something very specific and then do something kind of high speed, like task a drone to give you a visual assessment and then run object detection or facial recognition on, you know, do object detection to find a person and do facial recognition on that person to find out if that's a patrol walking through a field or a bad guy trying Thio invade your space. Um and so it's really the confluence and the gestalt of all of these sensors in the analytics working together, Um, that really creates the power from very simple, simple delivery. I think, um, there's this, You know, this idea that you know, ah 100 bytes of data is not that important. But when you put a million sensors giving you 100 bytes of data, you can truly find something extremely powerful. And then when you kind of and you make those interactions sing, um, it's amazing. Tow us the productivity that we can produce and the kind of fidelity of response that we can give thio actors in the space whether that's a defender trying to defend the base or a maintenance person trying thio proactively replace the fan or clean the fan on an H vac system. So So you know, you know, there isn't a fire at a base or for, uh, interesting enough. One of the things that we we've been able to achieve is we've taken maintenance data for helicopter engines and And we've been able to proactively say, Hey, you need to You need to take care of this part of the helicopter engine. Um and it saves money. It saves downtimes. It keeps the birds in the air. And it's a relatively simple algorithm that we were able to achieve. And we were able to do that with the maintenance people, bring them along in this endeavor and create analytics that they understood and could trust on DSO. I think that's really the power of this base. >>Tremendous power. I wish we had more time to to dig into it. Guys, thank you so much for sharing. Not just your insights, what nobody is doing but your passion for what you're doing and how you're making such an impact. Your passion is definitely palpable. Steven. Kevin, Thank you for joining me today. >>Thank you >>for my guests. I'm Lisa Martin. You're watching the Cube? Virtual. Yeah,

>> Announcer: From around the globe, it's theCUBE, with digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS Worldwide Public Sector. >> Welcome to theCUBE Virtual and our coverage of AWS re:Invent 2020, the specialized programming for Worldwide Public Sector. I'm Lisa Martin. I'm joined by Nick Speece the chief federal technologist for Snowflake. Nick, welcome to theCUBE. >> Thank you, Lisa. It's great to be here. >> Likewise, chief federal technologist, that's the first time I've ever heard of that title. Tell me a little bit about that. >> It's probably the last time you'll hear it. So chief federal technologist is really somebody in the company who is focused on bringing the needs of the federal government back to our corporate headquarters, making sure that the product as it's developed and evolves has the federal requirements in mind. >> Excellent. So the last couple of months for Snowflake big, biggest software IPO and software history your market cap right now is at 66 billion 515 data workloads running on Snowflake's platform every day 250 petabytes of data under management, a lot is going on. Let's talk about Snowflake. You guys operate only in the cloud, why was that decision made and how does that impact businesses analysis of data? >> Yeah, so great question and the answer is actually in the opening that you gave for us and thank you for that reinforcement. Snowflake can't exist anywhere, but the cloud. Technology over the last five to 10 years has really seen a move from what the cloud originally was, which was I have a virtual machine in my data center, I'm going to run it on your stuff not mine, into more comprehensive service offerings like Snowflake. We can't reach the kind of scale that Snowflake operates at every day and that our customers demand without the technology of clouds like AWS. The technology has to be there, the underlying and underpinning architecture has to be there, otherwise our customers get left in the dark and we can't can't have that. >> And especially today as data volumes are massively increasing and we know that that's only going to go up. We know that IT is only going to be more complex but when we talk to businesses in any industry the value of the data is in the insights the ability to extract that data in real time glean insights from it so that businesses can make data-based decisions that pivot their business, especially critical during the year that we have now known as 2020. Talk to me a little bit about though digging into your marketing material, everyone, there's all these terms, right, that everyone uses and you guys use single source of truth. What does it actually mean for single source, for stuff like? >> Yeah, so we talk about cloud, we talk about single source of truth and when you're looking at data problems, the problem and the solution are the same thing. A massive amount of data is a raw resource, that's all it is. And trying to refine that raw resource into something that is insightful or something that is useful to a business process is a challenge that every customer in every market, in every region undergoes. And how you overcome that is critical. And one of the primary focuses of Snowflake is to evolve the data cloud. Snowflake platform is the underlying technology for the data cloud but the data cloud is where we're going. And what I mean by data cloud. If you have a data set, your internal data, that is your truth, but it might not be the truth. So in Snowflake we encourage our customers to collaborate on data sets. For example, if you want to know how many people are living in a certain borough in New York City you could go around with a clicker and count everyone, or you could just ask the Census Bureau. That's the nature of the data cloud and what we're talking about here. Going to the subject matter experts who have the data that you need, using our marketplace, using our private exchanges, using our data sharing to build your own data cloud and become part of the next gen architecture for data sharing and collaboration, to get to the source of the truth, to make better decisions, to gain better insights. It's great to combine your data with enrich data from other sources, especially when it comes to making federal decisions and governance decisions. >> Absolutely that's critical. That the biggest challenge customers have is being able to sort through all that and find. I like how you put this as their single source of truth. Can you give us some examples of some federal agencies maybe even just anonymously that are using the power of Snowflake to do just that? >> Absolutely. We've got customers in the healthcare space and in some of the law enforcement spaces and especially in public education that are trying to increase the awareness of the folks that are subscribing to their services, for example, folks that are looking for healthcare help. If you're filing claims for a certain healthcare providers or certain care facilities, we want to make sure that those claims that are forwarded to those entities are legitimate, first of all, for example, if you're filing a claim for knee surgery in Florida, you probably didn't have one in California, three hours later. So those kinds of enforcement activities, and not just trying to do audits but also to benefit everybody who's receiving care. There's a lot of push now about genetic sequencing, DNA and RNA vaccination is huge with COVID-19, getting access to massive amounts of data to do analysis against and figure out the best approach, that's critical for where we go in the next 10 to 15 years in healthcare. Snowflake is very, very honored and happy to be propelling that move in the healthcare space. >> It is that's going to be absolutely critical but we're also seeing it, you know, everywhere else, such as for universities and education, suddenly this need, the last few months for real-time learning. Talk to me about data analysis. Can Snowflake help companies, you talked about enriching data sets so not just companies sources of data but additional data sets that they can add in and evaluate and analyze to make great decisions, but from a historical real-time perspective, talk to me how Snowflake helps with that data analysis. >> Yeah, sure. Right. So Snowflake in and of itself can do some analysis work. We've got some great visualization tools in our new UI that was released recently on public preview. So there's some analysis tools built into Snowflake but really where the value comes from is in taking your tools that you already use today and connecting it to a data source or platform that can wrangle that data, that can move that data through automated pipelines to give you a model view of that data that's beneficial. For example, data scientists and data engineers spend 80% of their time, and I know a lot of statistics are made up on the spot, that was not a promise, but trying to move this data through and refine it and build features to get to the point where you can ask a question is 80% of these very valuable professionals time. Shortening those timelines is what Snowflake really aims to do in the analysis space. We're not trying to replace the analysis tools that you use today, we work fine with all of them. The big difference is presenting them with enough data volume to give you real insights and eliminate bias as much as we can in data sets. >> What are some of the things that differentiates Snowflake from data warehouses and other folks in the market? >> Yeah. Great question. The big difference is Snowflake was built natively for the cloud. We weren't adapted to the cloud, we didn't adopt the cloud at some point in the future, Snowflake was built from scratch to be in the cloud. And since this is the appropriate show to mention it the primary difference between us is we were built to use object storage foundationally underneath our technology. And I know that sounds really nerdy and it is, but it adds a tremendous amount of value. If you think about how we used to collaborate 10 years ago we'd have a spreadsheet that if I open that spreadsheet for my share drive and you tried to open it at the same time, you'd get locked out. You're told you couldn't have it. And if tradition stays true I would probably be on vacation for two weeks. Contrast that now with the massive Google Doc platform and Office 365, object storage has changed the way that we collaborate on the same kinds of documents. Multiple people interacting with one thing at one time without contention, that's the reason why Snowflake has to operate in the cloud. We bring that same paradigm, multiple actors on a single object and give you that source of truth the truth that you absolutely need to make decisions. >> And that's critical these days as we know. We're in living in uncertain times and one of the things I think we can expect is the uncertainty to continue, but also for many industries people to stay remote or some big percentage for quite a while. So the ability to have those collaboration tools and be able to collaborate in real time is table stakes for so many companies. But when we're talking about some of the things going on this year, security, we can't not talk about security. You know, all these folks from home accessing corporate networks, you know, maybe not through VPNs or behind firewalls, the cloud is paramount to that. How does Snowflake address the security issue? >> Absolutely. So I'll start by saying our security is inherited from the wonderful security platform that AWS has underneath it. So we inherit all the security around data storage the EC Compute, all of the different entities and end points that AWS already secures Snowflake takes the same precautions. More than that, we've also built and rolled this access control to ensure that people are getting access only to the data that they should be getting access to, we recently implemented data masking as well, so certain roles are not able to see unmasked data, but they can still do queries that use the underlying data to filter. So there's a lot of different capabilities built in, encryption at rest, encryption in flight, AES-256 encryption keys used in a hierarchial model. These are phenomenal security architectures that are paramount to the security of the folks that are using our platform. Because we know at the end of the day the first day we have a leak in Snowflake is probably our last day in business. We got to be good at that which is why it's our top priority. >> I didn't, to ever talk about security as an inherited, I must be a dominant trait if we're going to be talking about, you know, genetics and chromosomes and mRNA and things like that. So walk me through last question, a government organization, or say they're an AWS customer or they want to start using Snowflake, what's that process? How do they go about doing that to leverage those inherited security capabilities that you talked about? >> Well, thankfully AWS has helped us put a FedRAMP moderate certified Snowflake region together in AWS, East commercial, so we're very happy to have a FedRAMP moderate region. They can access Snowflake through the AWS Marketplace or from Snowflake.com, you can start a trial in just a couple of minutes. Our security is built into all of our regions although the FedRAMP regions are specialized in some of the encryption technology we use, but we always, always always protect our users' data, regardless of where it is. >> You make it sound easy, I got to say. (laughing) >> That's because it is. (laughing) Thank you cloud. >> That's good. And well, that's good and it should be, especially because there's so much complexity and uncertainty everywhere else in the world right now. Last question for you. As I mentioned in the beginning, the biggest IPO in software history, just a couple of months ago during probably one of the most strangest time of any of us have ever, and our relatives ever witnessed, what can we expect from Snowflake in 2021? Are you going to bring all the good vibes that we all need? (laughing) >> Well, good vibes is our business model. You know, Snowflake is a phenomenal platform. We've had a ton of success driven by the success of our cloud provider partners, driven by the success of our wonderful customers. We have over 4,000 people using Snowflake now to great effect. You can look for more features, you can look for more functions, but really the evolution of the data cloud, our big push is to help our customers get into the data cloud, get the truth out of their data and make better decisions every day. And you'll see more of that from us as time continues. >> One more question I wanted to sneak in, how did you work with those customers to evolve the data cloud? What's that feedback loop like? >> It's, a lot of it comes down to silos that the customers have built up over years and years and years of operation. That's the first step. In Snowflake there isn't such thing really as a data silo there's data put into Snowflake, everything is unified, you can do queries across databases, that's the first thing. The second thing is browsing our data marketplace. It's just like an App Store for your phone but instead it's data sets and the data sets are published by the experts who know that material better than anyone. I mentioned earlier bringing in everything from housing evaluation data to COVID-19 data from California and Boston, bringing World Health Organization data, John Hopkins University data, joining that with the data that you already use today along with weather and population counts, the main thing here, the strategy is almost endless. More and more data sets are being published over every day. We have over a hundred contributors in the marketplace now. >> That's exciting that we have the technology and the power like this to help the world re, you know, recover from such a crazy time. It's nice to know that, that there was the power of that behind that, and the smart folks like you chief federal technologists, helping to fine tune that and really ensure that organizations across the government can maximize the value of data and find their single source of truth. Nick, it's been a blast having you on theCUBE. Thank you for joining me. >> Thank you for having me. >> For next piece, I'm Lisa Martin. You're watching theCUBE Virtual. (upbeat music)