>> Announcer: From around the globe, it's theCUBE. With digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS global partner network. >> Okay, welcome back everyone to theCUBE virtual coverage of re:Invent 2020 virtual. Normally we're in person, this year because of the pandemic we're doing remote interviews and we've got a great coverage here of the APN, Amazon Partner Network experience. I'm your host John Furrier, we are theCUBE virtual. Got a great guest from Tel Aviv remotely calling in and videoing, Nimrod Vax, who is the chief product officer and co-founder of BigID. This is the beautiful thing about remote, you're in Tel Aviv, I'm in Palo Alto, great to see you. We're not in person but thanks for coming on. >> Thank you. Great to see you as well. >> So you guys have had a lot of success at BigID, I've noticed a lot of awards, startup to watch, company to watch, kind of a good market opportunity data, data at scale, identification, as the web evolves beyond web presence identification, authentication is super important. You guys are called BigID. What's the purpose of the company? Why do you exist? What's the value proposition? >> So first of all, best startup to work at based on Glassdoor worldwide, so that's a big achievement too. So look, four years ago we started BigID when we realized that there is a gap in the market between the new demands from organizations in terms of how to protect their personal and sensitive information that they collect about their customers, their employees. The regulations were becoming more strict but the tools that were out there, to the large extent still are there, were not providing to those requirements and organizations have to deal with some of those challenges in manual processes, right? For example, the right to be forgotten. Organizations need to be able to find and delete a person's data if they want to be deleted. That's based on GDPR and later on even CCPA. And organizations have no way of doing it because the tools that were available could not tell them whose data it is that they found. The tools were very siloed. They were looking at either unstructured data and file shares or windows and so forth, or they were looking at databases, there was nothing for Big Data, there was nothing for cloud business applications. And so we identified that there is a gap here and we addressed it by building BigID basically to address those challenges. >> That's great, great stuff. And I remember four years ago when I was banging on the table and saying, you know regulation can stunt innovation because you had the confluence of massive platform shifts combined with the business pressure from society. That's not stopping and it's continuing today. You seeing it globally, whether it's fake news in journalism, to privacy concerns where modern applications, this is not going away. You guys have a great market opportunity. What is the product? What is smallID? What do you guys got right now? How do customers maintain the success as the ground continues to shift under them as platforms become more prevalent, more tools, more platforms, more everything? >> So, I'll start with BigID. What is BigID? So BigID really helps organizations better manage and protect the data that they own. And it does that by connecting to everything you have around structured databases and unstructured file shares, big data, cloud storage, business applications and then providing very deep insight into that data. Cataloging all the data, so you know what data you have where and classifying it so you know what type of data you have. Plus you're analyzing the data to find similar and duplicate data and then correlating them to an identity. Very strong, very broad solution fit for IT organization. We have some of the largest organizations out there, the biggest retailers, the biggest financial services organizations, manufacturing and et cetera. What we are seeing is that there are, with the adoption of cloud and business success obviously of AWS, that there are a lot of organizations that are not as big, that don't have an IT organization, that have a very well functioning DevOps organization but still have a very big footprint in Amazon and in other kind of cloud services. And they want to get visibility and they want to do it quickly. And the SmallID is really built for that. SmallID is a lightweight version of BigID that is cloud-native built for your AWS environment. And what it means is that you can quickly install it using CloudFormation templates straight from the AWS marketplace. Quickly stand up an environment that can scan, discover your assets in your account automatically and give you immediate visibility into that, your S3 bucket, into your DynamoDB environments, into your EMR clusters, into your Athena databases and immediately building a full catalog of all the data, so you know what files you have where, you know where what tables, what technical metadata, operational metadata, business metadata and also classified data information. So you know where you have sensitive information and you can immediately address that and apply controls to that information. >> So this is data discovery. So the use case is, I'm an Amazon partner, I mean we use theCUBE virtuals on Amazon, but let's just say hypothetically, we're growing like crazy. Got S3 buckets over here secure, encrypted and the rest, all that stuff. Things are happening, we're growing like a weed. Do we just deploy smallIDs and how it works? Is that use cases, SmallID is for AWS and BigID for everything else or? >> You can start small with SmallID, you get the visibility you need, you can leverage the automation of AWS so that you automatically discover those data sources, connect to them and get visibility. And you could grow into BigID using the same deployment inside AWS. You don't have to switch migrate and you use the same container cluster that is running inside your account and automatically scale it up and then connect to other systems or benefit from the more advanced capabilities the BigID can offer such as correlation, by connecting to maybe your Salesforce, CRM system and getting the ability to correlate to your customer data and understand also whose data it is that you're storing. Connecting to your on-premise mainframe, with the same deployment connecting to your Google Drive or office 365. But the point is that with the smallID you can really start quickly, small with a very small team and get that visibility very quickly. >> Nimrod, I want to ask you a question. What is the definition of cloud native data discovery? What does that mean to you? >> So cloud native means that it leverages all the benefits of the cloud. Like it gets all of the automation and visibility that you get in a cloud environment versus any traditional on-prem environment. So one thing is that BigID is installed directly from your marketplace. So you could browse, find its solution on the AWS marketplace and purchase it. It gets deployed using CloudFormation templates very easily and very quickly. It runs on a elastic container service so that once it runs you can automatically scale it up and down to increase the scan and the scale capabilities of the solution. It connects automatically behind the scenes into the security hub of AWS. So you get those alerts, the policy alerts fed into your security hub. It has integration also directly into the native logging capabilities of AWS. So your existing Datadog or whatever you're using for monitoring can plug into it automatically. That's what we mean by cloud native. >> And if you're cloud native you got to be positioned to take advantage of the data and machine learning in particular. Can you expand on the role of machine learning in your solution? Customers are leaning in heavily this year, you're seeing more uptake on machine learning which is basically AI, AI is machine learning, but it's all tied together. ML is big on all the deployments. Can you share your thoughts? >> Yeah, absolutely. So data discovery is a very tough problem and it has been around for 20 years. And the traditional methods of classifying the data or understanding what type of data you have has been, you're looking at the pattern of the data. Typically regular expressions or types of kind of pattern-matching techniques that look at the data. But sometimes in order to know what is personal or what is sensitive it's not enough to look at the pattern of the data. How do you distinguish between a date of birth and any other date. Date of birth is much more sensitive. How do you find country of residency or how do you identify even a first name from the last name? So for that, you need more advanced, more sophisticated capabilities that go beyond just pattern matching. And BigID has a variety of those techniques, we call that discovery-in-depth. What it means is that very similar to security-in-depth where you can not rely on a single security control to protect your environment, you can not rely on a single discovery method to truly classify the data. So yes, we have regular expression, that's the table state basic capability of data classification but if you want to find data that is more contextual like a first name, last name, even a phone number and distinguish between a phone number and just a sequence of numbers, you need more contextual NLP based discovery, name entity recognition. We're using (indistinct) to extract and find data contextually. We also apply deep learning, CNN capable, it's called CNN, which is basically deep learning in order to identify and classify document types. Which is basically being able to distinguish between a resume and a application form. Finding financial records, finding medical records. So RA are advanced NLP classifiers can find that type of data. The more advanced capabilities that go beyond the smallID into BigID also include cluster analysis which is an unsupervised machine learning method of finding duplicate and similar data correlation and other techniques that are more contextual and need to use machine learning for that. >> Yeah, and unsupervised that's a lot harder than supervised. You need to have that ability to get that what you can't see. You got to get the blind spots identified and that's really the key observational data you need. This brings up the kind of operational you heard cluster, I hear governance security you mentioned earlier GDPR, this is an operational impact. Can you talk about how it impacts on specifically on the privacy protection and governance side because certainly I get the clustering side of it, operationally just great. Everyone needs to get that. But now on the business model side, this is where people are spending a lot of time scared and worried actually. What the hell to do? >> One of the things that we realized very early on when we started with BigID is that everybody needs a discovery. You need discovery and we actually started with privacy. You need discovery in route to map your data and apply the privacy controls. You need discovery for security, like we said, right? Find and identify sensitive data and apply controls. And you also need discovery for data enablement. You want to discover the data, you want to enable it, to govern it, to make it accessible to the other parts of your business. So discovery is really a foundation and starting point and that you get there with smallID. How do you operationalize that? So BigID has the concept of an application framework. Think about it like an Apple store for data discovery where you can run applications inside your kind of discovery iPhone in order to run specific (indistinct) use cases. So, how do you operationalize privacy use cases? We have applications for privacy use cases like subject access requests and data rights fulfillment, right? Under the CCPA, you have the right to request your data, what data is being stored about you. BigID can help you find all that data in the catalog that after we scan and find that information we can find any individual data. We have an application also in the privacy space for consent governance right under CCP. And you have the right to opt out. If you opt out, your data cannot be sold, cannot be used. How do you enforce that? How do you make sure that if someone opted out, that person's data is not being pumped into Glue, into some other system for analytics, into Redshift or Snowflake? BigID can identify a specific person's data and make sure that it's not being used for analytics and alert if there is a violation. So that's just an example of how you operationalize this knowledge for privacy. And we have more examples also for data enablement and data management. >> There's so much headroom opportunity to build out new functionality, make it programmable. I really appreciate what you guys are doing, totally needed in the industry. I could just see endless opportunities to make this operationally scalable, more programmable, once you kind of get the foundation out there. So congratulations, Nimrod and the whole team. The question I want to ask you, we're here at re:Invent's virtual, three weeks we're here covering Cube action, check out theCUBE experience zone, the partner experience. What is the difference between BigID and say Amazon's Macy? Let's think about that. So how do you compare and contrast, in Amazon they say we love partnering, but we promote our ecosystem. You guys sure have a similar thing. What's the difference? >> There's a big difference. Yes, there is some overlap because both a smallID and Macy can classify data in S3 buckets. And Macy does a pretty good job at it, right? I'm not arguing about it. But smallID is not only about scanning for sensitive data in S3. It also scans anything else you have in your AWS environment, like DynamoDB, like EMR, like Athena. We're also adding Redshift soon, Glue and other rare data sources as well. And it's not only about identifying and alerting on sensitive data, it's about building full catalog (indistinct) It's about giving you almost like a full registry of your data in AWS, where you can look up any type of data and see where it's found across structured, unstructured big data repositories that you're handling inside your AWS environment. So it's broader than just for security. Apart from the fact that they're used for privacy, I would say the biggest value of it is by building that catalog and making it accessible for data enablement, enabling your data across the board for other use cases, for analytics in Redshift, for Glue, for data integrations, for various other purposes. We have also integration into Kinesis to be able to scan and let you know which topics, use what type of data. So it's really a very, very robust full-blown catalog of the data that across the board that is dynamic. And also like you mentioned, accessible to APIs. Very much like the AWS tradition. >> Yeah, great stuff. I got to ask you a question while you're here. You're the co-founder and again congratulations on your success. Also the chief product officer of BigID, what's your advice to your colleagues and potentially new friends out there that are watching here? And let's take it from the entrepreneurial perspective. I have an application and I start growing and maybe I have funding, maybe I take a more pragmatic approach versus raising billions of dollars. But as you grow the pressure for AppSec reviews, having all the table stakes features, how do you advise developers or entrepreneurs or even business people, small medium-sized enterprises to prepare? Is there a way, is there a playbook to say, rather than looking back saying, oh, I didn't do with all the things I got to go back and retrofit, get BigID. Is there a playbook that you see that will help companies so they don't get killed with AppSec reviews and privacy compliance reviews? Could be a waste of time. What's your thoughts on all this? >> Well, I think that very early on when we started BigID, and that was our perspective is that we knew that we are a security and privacy company. So we had to take that very seriously upfront and be prepared. Security cannot be an afterthought. It's something that needs to be built in. And from day one we have taken all of the steps that were needed in order to make sure that what we're building is robust and secure. And that includes, obviously applying all of the code and CI/CD tools that are available for testing your code, whether it's (indistinct), these type of tools. Applying and providing, penetration testing and working with best in line kind of pen testing companies and white hat hackers that would look at your code. These are kind of the things that, that's what you get funding for, right? >> Yeah. >> And you need to take advantage of that and use them. And then as soon as we got bigger, we also invested in a very, kind of a very strong CSO that comes from the industry that has a lot of expertise and a lot of credibility. We also have kind of CSO group. So, each step of funding we've used extensively also to make RM kind of security poster a lot more robust and invisible. >> Final question for you. When should someone buy BigID? When should they engage? Is it something that people can just download immediately and integrate? Do you have to have, is the go-to-market kind of a new target the VP level or is it the... How does someone know when to buy you and download it and use the software? Take us through the use case of how customers engage with. >> Yeah, so customers directly have those requirements when they start hitting and having to comply with regulations around privacy and security. So very early on, especially organizations that deal with consumer information, get to a point where they need to be accountable for the data that they store about their customers and they want to be able to know their data and provide the privacy controls they need to their consumers. For our BigID product this typically is a kind of a medium size and up company, and with an IT organization. For smallID, this is a good fit for companies that are much smaller, that operate mostly out of their, their IT is basically their DevOps teams. And once they have more than 10, 20 data sources in AWS, that's where they start losing count of the data that they have and they need to get more visibility and be able to control what data is being stored there. Because very quickly you start losing count of data information, even for an organization like BigID, which isn't a bigger organization, right? We have 200 employees. We are at the point where it's hard to keep track and keep control of all the data that is being stored in all of the different data sources, right? In AWS, in Google Drive, in some of our other sources, right? And that's the point where you need to start thinking about having that visibility. >> Yeah, like all growth plan, dream big, start small and get big. And I think that's a nice pathway. So small gets you going and you lead right into the BigID. Great stuff. Final, final question for you while I gatchu here. Why the awards? Someone's like, hey, BigID is this cool company, love the founder, love the team, love the value proposition, makes a lot of sense. Why all the awards? >> Look, I think one of the things that was compelling about BigID from the beginning is that we did things differently. Our whole approach for personal data discovery is unique. And instead of looking at the data, we started by looking at the identities, the people and finally looking at their data, learning how their data looks like and then searching for that information. So that was a very different approach to the traditional approach of data discovery. And we continue to innovate and to look at those problems from a different perspective so we can offer our customers an alternative to what was done in the past. It's not saying that we don't do the basic stuffs. The Reg X is the connectivity that that is needed. But we always took a slightly different approach to diversify, to offer something slightly different and more comprehensive. And I think that was the thing that really attracted us from the beginning with the RSA Innovation Sandbox award that we won in 2018, the Gartner Cool Vendor award that we received. And later on also the other awards. And I think that's the unique aspect of BigID. >> You know you solve big problems than certainly as needed. We saw this early on and again I don't think that the problem is going to go away anytime soon, platforms are emerging, more tools than ever before that converge into platforms and as the logic changes at the top all of that's moving onto the underground. So, congratulations, great insight. >> Thank you very much. >> Thank you. Thank you for coming on theCUBE. Appreciate it Nimrod. Okay, I'm John Furrier. We are theCUBE virtual here for the partner experience APN virtual. Thanks for watching. (gentle music)

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation LeBron welcome to the cube studio I'm John Ferrier here in Palo Alto in our remote coverage of the tech industry we are in our quarantine crew here getting all the stories in the technology industry from all the thought leaders and all the newsmakers we've got a great story here about data data compliance and really about the platforms around how enterprises are using data I've got two great guests and some news to announce Kieran our CEO is the vice president of business development with elation and William Murphy vice president of technology alliances of big ID got some interesting news a integration partnership between the two companies really kind of compelling especially now as people have to look at the cloud scale what's happening in our world certainly in the new realities of kovin 19 and going forward the role of data new kinds of applications and the speed and agility are gonna require more and more automation more reality around making sure things are in place so guys thanks for coming on appreciate it Kieran William thanks for joining me thank you thank you so let's take a step back elation you guys have been on the cube many times we've been following you guys been a leader and Enterprise catalog a new approach it's a real new technology approach and methodology and team approach to building out the data catalogues so talk about the Alliance here why what's the news why you guys in Creighton is integration partnership well let me start and thank you for having us today you know as you know elation launched the data catalog a category seven years ago and even today we're acknowledging the leader as a leader in that space you know and but we really began with the core belief that ultimately data management will be drive driven more and more by business demand and less by information suppliers so you know another way to think about that is you know how people behave with data will drive how companies manage data so our philosophy put very simply is to start with people and not first not data and our customers really seem to agree with this approach and we've got close to 200 brands using our data you know our tool every single day to drive vibrant data communities and and foster a real data culture in the environment so one of the things that was really exciting to us is the in been in data privacy by large corporate customers to get their arms around this and you know we really strive to improve our ability to use the tool inside you know these enterprises across more use cases so the partnership that we're announcing with big ID today is really you know Big Ideas the leading modern data intelligence platform for privacy and what we're trying to do is to bring bring a level of integration between our two technologies so that enterprises in better manage and scale their their data privacy compliance capability William talked about big ID what you guys are doing you guys also have a date intelligence platform we've been covering gdpr for a very long time I once called I won't say it again because it wasn't really that complimentary but the reality has sit in and they and the users now understand more than ever privacy super important companies have to deal with this you guys have a solution take a minute to explain big-big ID and what you guys are doing yeah absolutely so our founders Demetri Shirota and Nimrod Beck's founded big idea in 2016 Sam you know gdpr was authored and the big reason there is that data changed and how companies and enterprises doubled data was changing pretty much forever that profound change meant that the status quo could no longer exist and so privacy was gonna have to become a day-to-day reality to these enterprises but what big ID realized is that to start to do to do anything with privacy you actually have to understand where your data is what it is and whose it is and so that's really the genesis of what dimitri nimrod created which which is a privacy centric data discovery and intelligence platform that allows our enterprise customers and we have over 70 customers in the enterprise space many within the Fortune hundred to be able to find classify and correlate sensitive data as they defined it across data sources whether its own Prem or in the cloud and this gives our users and kind of unprecedented ability to look into their data to get better visibility which if both allows for collaboration and also allows for real-time decision-making a big place with better accuracy and confidence that regulations are not being broken and that customers data is being treated appropriately great I'm just reading here from the release that I want to get you guys thoughts and unpack some of the concepts on here but the headline is elation strengthens privacy capabilities with big ID part nur ship empowering organizations to mitigate risks delivering privacy aware data use and improved adherence to data privacy regulations it's a mouthful but the bottom line is is that there's a lot of stuff to that's a lot of complexity around these rules and these platforms and what's interesting you mentioned discovery the enterprise discovery side of the business has always been a complex nightmare I think what's interesting about this partnership from my standpoint is that you guys are bringing an interface into a complex platform and creating an easy abstraction to kind of make it usable I mean the end of the day you know we're seeing the trends with Amazon they have Kendre which they announced and they're gonna have a ship soon fast speed of insights has to be there so unifying data interfaces with back-end is really what seems to be the pattern is that the magic going on here can you guys explain what's going on with this and what's the outcome gonna be for customers yeah I guess I'll kick off and we'll please please chime in I think really there's three overarching challenges that I think enterprises are facing is they're grappling with these regulations as as we'll talked about you know number one it's really hard to both identify and classify private data right it's it's not as easy as it might sound and you know we can talk a little bit more about that it's also very difficult to flag at the point of analysis when somebody wants to find information the relevant policies that might apply to the given data that they're looking to it to run an analysis on and lastly the enterprise's are constantly in motion as enterprises change and by new businesses and enter new markets and launch new products these policies have to keep up with that change and these are real challenges to address and you know with Big Idea halation we're trying to really accelerate that compliance right with the the you know the combination of our tools you know reduce the the cost and complexity of compliance and fundamentally keep up through a single interface so that users can know what to do with data at the point of consumption and I think that's the way to think about it well I don't know if you want to add something to that absolutely I think when Karen and I have been working on this for actually many months at this point but most companies don't have a business plan of just saying let's store as much data as possible without getting anything out of it but in order to get something out of it the ability to find that data rapidly and then analyze it so that decision makers make up-to-date decisions is pretty vital a lot of these things when they have to be done manually take a long time they're huge business issues there and so the ability to both automate data discovery and then cataloging across elation and big ID gives those decision makers whether the data steward the data analyst the chief data officer an ability to really dive deeper than they have previously with better speed you know one of the things that we've been talking about for a long time with big data as these data links and they're fairly easy to pull I mean you can put a bunch of data into a corpus and you you act on them but as you start to get across these silos there's a need for you know getting a process down around managing just not only the data wrangling but the policies behind it and platforms are becoming more complex can you guys talk about the product market fit here because there's sass involved so there's also a customer activity what's the product market fit that you guys see with this integration what are some of the things that you're envisioning to emerge out of this value proposition I think I can start I think you're exactly right enterprises have made huge investments in you know historically data warehouses data Mart's data lakes all kinds of other technology infrastructure aimed at making the data easier to get to but they've effectively just layered on to the problem so elations catalog has made it incredibly much more effective at helping organizations to find to understand trust to reuse and use that data so that stewards and people who know about the data can inform users who may need need to run a particular report or conduct a specific analysis can accelerate that process and compress the time the insights much much more than then it's are possible with today's technologies and if you if you overlay that on to the data privacy challenge its compounded and I think you know will it would be great for you to comment on what the data discovery capability it's a big ID do to improve that that even further yeah absolutely so as to companies we're trying to bridge this gap between data governance and privacy and and John as you mentioned there's been a proliferation of a lot of tools whether their data lakes data analysis tools etc what Big Idea is able to do is we're looking across over 70 different types of data platforms whether they be legacy systems like SharePoint and sequel whether they be on pram or in the cloud whether it's data at rest or in motion and we're able to auto populate our metadata findings into relations data catalog the main purpose there being that those data stewards and have access to the most authentic real time data possible so on the terms of the customer value they're going to see what more built in privacy aware features is its speed but you know what I mean the problem is compounded with the data getting that catalog and getting insights out of it but for this partnership is it speed to outcome what does the outcome that you guys are envisioning here for the customer I think it's a combination of speed as you said you know they can much more rapidly get up to speed so an analyst who needs to make a decision about specific data set whether they can use it or not and know at the point of analysis if this data is governed by policies that has been informed by big IDs so the elation catalog user can make a much more rapid decision about how to use that the second piece is the complexity and costs of compliance they can really reduce and start to winnow down their technology footprint because with the combination of the discovery that big ID provides the the the ongoing discovery the big ID provides and the enterprise it data catalog provided violation we give the framework for being able to keep up with these changes in policies as rules and as companies change so they don't have to keep reinventing the wheel every time so we think that there's a significant speed time the market advantage as well as an ability to really consolidate technology footprint well I'll add to that yeah yeah just one moment so elation when they helped create this marketplace seven years ago one of the goals there and I think we're Big Ideas assisting as well as the trusting confidence that both the users of these software's the data store of the analysts have and the data that they're using and then the the trust and confidence are building with their end consumers is much better knowing that there is the this is both bi-directional and ongoing continuously you know I've always been impressed with relations vision it's big vision around the role of the human and data and it's always been impressive and yeah I think the world spinning in that direction you starting to see that now William I want to get your thoughts with big id because you know one of the things is challenging out there from what we're hearing is you know people want to protect the sensitive data obviously with the hacks and everything else and personal information there's all kinds of regulation and believe me state by state nation by nation it's crazy complex at the same time they've got to ensure this compliance tripwires everywhere right so you have this kind of nested complex web of stuff and some real security concerns at the same time you want to make data available for machine learning and for things like that this is the real kind of things that the problem has twisted around so if I'm an enterprise I'm like oh man this is a pain in the butt so how are you guys seeing this evolve because this solution is one step in that direction what are some of the pain points what are some of the examples can you share any insights around how people are overcoming that because they want to get the data out there they want to create applications that are gonna be modern robust and augmented with whether it's augmented AI of some sort or some sort of application at the same time protecting the information and compliance it's a huge problem challenge your thoughts absolutely so to your point regulations and compliance measures both state-by-state and internationally they're growing I mean I think when we saw GDP our four years ago in the proliferation of other things whether it be in Latin America in Asia Pacific or across the United States potentially even at the federal level in the future it's not making it easier to add complexity to that every industry and many companies individually have their own policies in the way that they describe data whether what's sensitive to them is it patent numbers is it loyalty card numbers is it any number of different things where they could just that that enterprise says that this type of data is particularly sensitive the way we're trying to do this is we're saying that if we can be a force multiplier for the individuals within our organization that are in charge of the stewardship over their data whether it be on the privacy side on the security side or on the data and analytics side that's what we want to do and automation is a huge piece of this so yes the ID has a number of patents in the machine learning area around data discovery and classification cluster analysis being able to find duplicate of data out there and when we put that in conjunction with what elations doing and actually gave the users of the data the kind of unprecedented ability to curate deduplicate secure sensitive data all by a policy driven automated platform that's actually I think the magic gear is we want to make sure that when humans get involved their actions can be made how do I say this minimum minimum human interaction and when it's done it's done for a reason of remediation so they're there the second step not the first step here I'll get your thoughts you know I always riff on the idea of DevOps and it's a cloud term and when you apply that the data you talk about programmability scale automation but the humans are making calls whether you're a programmer and devops world or to a data customer of the catalog and halation i'm making decisions with my business I'm a human I'm taking action at the point of design or whatever this is where I think the magic can happen your thoughts on how this evolves for that use case because what you're doing is you're augmenting the value for the user by taking advantage of these things is is that right or am i around the right area yeah I think so I think the one way to think about elation and that analogy is that the the biggest struggle that enterprise business users have and we target the the consumers of data we're not a provider to the information suppliers if you will but the people who had need to make decisions every single day on the right set of data we're here to empower them to be able to do that with the data that they know has been given the thumbs up by people who know about the data connecting stewards who know about the subject matter at hand with the data that the analyst wants to use at the time of consumption and that powerful connection has been so effective in our customers that enabling them to do in our analytical work that they just couldn't dream of before so the key piece here is with the combination with big ID we can now layer in a privacy aware consumption angle which means if you have a question about running some customer propensity model and you don't know if you can use this data or that data the big ID data discovery platform informs the elation catalog of the usage capabilities of that given data set at the moment the analyst wants conduct his or her analysis with the appropriate data set as identified by the stewards and and as endorsed by the steward so that point in time is really critical because that's where the we can we can fundamentally shrink the decision sight yeah it's interesting and so have the point of attack on the user in this case the person in the business who's doing some real work that's where the action is yeah it's a whole nother meaning of actionable data right so you know this seems to where the values quits its agility really it's kind of what we're talking about here isn't it it is very agile on the differentiation between elation and big idea in what we're bringing to the market now is we're also bringing flexibility and you meant that the point of agility there is because we allow our customers to say what their policies are what their sense of gait is define that themselves within our platforms and then go out find that data classify and catalog at etc like that's giving them that extra flexibility the enterprise's today need so that it can make business decisions and faster and I actually operationalize data guys great job good good news it's I think this is kind of a interesting canary in the coal mine around the trends that are going on around how data is evolving what's next how you guys gonna go to market partnership obviously makes a lot of sense technical integration business model integration good fit what's next for you guys I'm sorry I mean I think the the great thing is that you know from the CEO down our organizations are very much aligned in terms of how we want to integrate our two solutions and how we want to go to market so myself and will have been really focused on making sure that the skill sets of the various constituents within both of our companies have the level of education and knowledge to bring these results to bear coupled with the integration of our two technologies well your thoughts yeah absolutely I mean between our CEOs who have a good cadence to care to myself who probably spend too much time on the phone at this point we might have to get him a guest bedroom or something alignments a huge key here ensuring that we've enabled our field to - and to evangelize this out to the marketplace itself and then doing whether it's this or our webinars or or however we're getting the news out it's important that the markets know that these capabilities are out there because the biggest obstacle honestly to adoption it's not that other solutions or build-it-yourself it's just lack of knowledge that it could be easier it could be done better that you could have you could know your data better you could catalog it better great final question to end the segment message to the potential customer out there what it what about their environment that might make them a great prospect for this solution is it is it a known problem is it a blind spot when would someone know to call you guys up in this to ship and leverage this partnership is it too much data as it's just too much many applications across geographies I'm just trying to understand the folks watching when it's an opportunity to call you guys welcome a relation perspective there that can never be too much data they the a signal that may may indicate an interest or a potential fit for us would be you know the need to be compliant with one or more data privacy regulations and as well said these are coming up left and right individual states in the in addition to the countries are rolling out data privacy regulations that require a whole set of capabilities to be in place and a very rigorous framework of compliance those those requirements and the ability to make decisions every single day all day long about what data to use and when and under what conditions are a perfect set of conditions for the use of a data catalog evacuation coupled with a data discovery and data privacy solution like big I well absolutely if you're an organization out there and you have a lot of customers you have a lot of employees you have a lot of different data sources and disparate locations whether they're on prime of the cloud these are solid indications that you should look at purchasing best-of-breed solutions like elation and Big Ideas opposed to trying to build something internally guys congratulations relations strengthening your privacy capabilities with the big ID partnership congratulations on the news and we'll we'll be tracking it thanks for coming I appreciate it thank you okay so cube coverage here in Palo Alto on remote interviews as we get through this kovat crisis we have our quarantine crew here in Palo Alto I'm John Fourier thanks for watching [Music] okay guys