Tony Coleman, Temenos and Boris Bialek, MongoDB | MongoDB World 2022
>>Yeah, yeah, yeah. We're back at the center of the coverage of the world 20 twenty-two, the first live event in three years. Pretty amazing. And I'm really excited to have Tony Coleman. Here is the c e o of those who changing the finance and banking industry. And this is the global head of industry solutions. That would be welcome. Back to the cube. Welcome. First time. Um, so thanks for coming on. Thank you. >>Thanks for having us, >>Tony. Tell us about what are you guys up to? Disrupting the finance world. >>So tomorrow is everyone's banking platform. So we are a software company. We have over 3000 financial institutions around the world. Marketing tell me that that works out is over 1.2 billion people rely on terminal software for their banking and financial needs. 41 of the top 50 banks in the world run software and we are very proud to be powering all of those entities on their innovation journeys and bringing you know, that digital transformation that we've seen so much all over the past few years and enabling a lot of the world's unbanked through digital banking become, you know, members of the >>community. So basically you're bringing the software platform to enable that to somebody you don't have to build it themselves because they never get there. Absolutely. And and so that's why I don't know if you consider that disruptive. I guess I do to the industry to a certain extent. But when you think of disruption in the business, you think of Blockchain and crypto, and 50 is that is completely separate world and you guys participate in that as well. Well, I >>would say it's related right? I mean, I was doing a podcast recently and they had this idea of, um, buzzword jail where you could choose words to go into jail and I said 50 not because I think they're intrinsically bad, but I think just at the moment they are a rife for scam area. I think it's one of those one of these technologies and investment area that people don't understand it, and there's a lot of a lot of mistakes that can be made in that, >>Yeah, >>I mean, it's a fascinating piece that it could be truly transformative if we get it right, but it's very emerging, so we'll see so don't play a huge part in the Blockchain industry directly. We work with partners in that space, but in terms of digital assets and that sort of thing. Yeah, absolutely. >>So, Boris, you have industry solutions in your title. What does that entail? So >>basically, I'm responsible for all the verticals, and that includes great partners like Tony. And we're doing a lot of verticals by now. When you listen. Today in all these various talks, we have so much stuff ranging from banking, go retail, healthcare, insurance, you name it, we have it by now. And that's obviously the clients moving from the edge solution. Like touching a little toe in the water, but longer to going all in building biggest solutions you saw on stage the lady from this morning. These are not second Great. Yeah, we do something small now. We're part of the transformation journey. And this is where Tony and I can regularly together how we transform things and how we built a new way of banking is done with Michael services and technology surrounding it. Yeah, >>but what about performance in this world? Can you tell me about that? >>Yeah. This is an interesting thing because people always challenging what is performance and document databases. And Tony challenged us actually, six weeks before his own show several weeks ago in London and says, Boris, let's do a benchmark And maybe you bring your story because if I get too excited, I follow. >>Yeah, sure, that performance and efficiency topics close close to my heart. I have been for for years. And so, yeah, we every two or three years, we run a high water. We've got a high water benchmark, and this year we sort of double down literally double down on everything we did previously. So this was 200 million accounts, 100 million customers, and we were thrashing through 102,800 seventy-five transactions a second, which is a phenomenal number. And, uh, >>can I do that on the Blockchain? >>Wow. Yeah, exactly. Right. So this is you know, I get asked why we do such high numbers and the reason is very straightforward. If somebody wants 10,000 transactions a second, we're seeing banks now that need that sort of thing. If I can give them a benchmark report, this is 100,000. I don't need to keep doing benchmarks. 10. >>Yeah. Tell me more about the Anytime you get into benchmarks, you want to understand the configuration. The workload. Tell me more about that. So we have >>a pretty well path of a standard transaction mix. We call it a retail transaction mix. And so it's the tries to the workload. Is that because it's a simulation right around what you would do in your daily basis? So you're going to make payments you're going to check? Your balance is you're going to see what he's moved on your account. So we do all of that and we run it through a proper production, good environment. And this is really important. This is something we do in the lab you couldn't go live on. This is all all of the horrible, non functional requirements around high availability, >>security, security passes, private wings, all these things. And one thing is, they're doing this for a long time. So this is not like let's define something new for the world. Now, this is something Tony's doing for literally 10, 15 years now, right? >>It was only 15 years, but this >>is your benchmark >>top >>developed Okay, >>so we run it through and, um yeah, some fantastic numbers. And not just on the share sort of top-level numbers 100,000 transactions. A second response time out of it was fantastic. One-millisecond, which is just brilliant. So it means you get these really efficient numbers what that helped us do with, you know, some of the other partners that are involved in the benchmark as well. It meant that our throughput court, which is a really good measure of efficiency, is up to four times better than we ran it three years ago. So in terms of a sustainability piece, which is so important that that's really a huge improvement, that's down to application changes, architect changes as well as using appropriate technology in the right place. >>How important? With things like the number, of course, the memory size is the block sizes. All that stuff. >>We are very tiny. So this is the part. When I talk to people, we have what we call a system in the back of people. Look at me. Um, how many transactions on that one? So, to be fair, three-quarters, we're going to be one quarter or something else because we're still putting some components of and start procedures for disclosure. But when I think Seventy-five 1000 transactions on a single single 80 system, which is thirty-two cause you're saying correctly, something like that. This is a tiny machine in the world of banking. So before this was the main friends and now it's wonderful instance on a W s. And this is really amazing. Costed and environmental footprint is so, so important >>and there's a heavy right heavy environment. >>So the the way we the way we architect the solution is it follows something called a command query responsibility, segregated segregation. So what we do, we do all the commands inappropriate database for that piece, and that was running at about Twenty-five 1000 transactions a second and then we're streaming the data out of that directly into So actually I was doing more than the Seventy-five 1000 queries. A second, which is the part of it was also investing Twenty-five 1000 transactions the second at the same time >>and okay, and the workload had a high locality medium locality. It was just give us a picture of what that's like. Sorry. So, >>yeah, >>we don't have that. Yeah, >>so explain that That's not That's not the mindset for a document. Exactly. >>Exactly. In the document database, you don't have the hot spotting the one single field off the table, which is suddenly hot spotting. And now you have literally and recovery comes up and we say, What goes, goes together, get together belongs together, comes out together. So the number of, for example, it's much, much smaller and the document system, then historically, relationship. >>So it is not a good good indicator, necessarily >>anymore. That's what this is so much reduced. The number of access patterns are smaller, and I mean it is highly optimized, for example, internally as well. The internal structures, so that was very close to a >>traditional benchmark, would have a cash in front of a high cash rate. So 100 and 99% right, That's a high locality reference. But that's that's irrelevant. >>It's gone. There's no cashing in the middle anymore. It goes straight against the database. All these things are out, and that's what makes it so exciting and all the things in a real environment. I think we really need to stress it. It's not a test that at home. It's a real life environment out into the wild with the benchmark driving and driving. >>How did your customers respond? You did this for your recent event? >>Yeah, we did it for our use. A conference, our community for, um, which was a few weeks ago in London. Um, and the You know, the reaction was Certainly it was a great reception, of course, but the main thing that people are fascinated about, how much more efficient the whole platform it's explaining. So you know when we can run and it's a great number that we've got the team pulled out, which is so having doubled throughput on the platform from what we did three years ago, we're actually using 20% less infrastructure to give double the performance. Uh, macro-level, that's a phenomenal achievement. And that means that these changes that we make everything that we're doing benefits all of our customers. So all of the banks, when they take the latest release, is they get these benefits. Everything is that much more efficient. So everybody benefits from every investment, >>and this was running in the cloud. Is that correct? You're running out of this. >>So this was list, Um, 80 on a W s with a W s cases and processes. And so it was a really reality driven environment, >>pure pure cloud-native or using mana services on a W s. And then at least for the peace. It's >>awesome. I mean, uh, So now how convenient for the timing from, uh, the world. How are you socializing with your community? >>We're having this afternoon session as well, where we talk a little bit more detail about that, and he has a session as well tomorrow. So we see a lot of good feedback as well when we bring it up with clients. Obviously some clients get very specific because this reduction footprint is so huge when you think a client has 89 environments from early development systems to production to emergency standby, maybe a different cloud. All these things what day talks about the different Atlas features multi cloud environmentally. All this stuff comes to play. And this is why I'm so excited to work with them. We should bring up as well the other things which are available to ready already with your front and solutions with Infinity services because that's the other part of the modernization, the Michael Services, which Tony so politely not mentioning. So there's a lot of cool technology into that one, which fits to how it works in micros services. Happy I first all these what they called factors. Micro service a p. I cloud-native headless. I think that was the right order now. So all these things are reflected as well. But with their leadership chief now, I think a lot of companies have to play Catch-up now to what Tony and his team are delivering on the bank. This >>gets the modernization. We really haven't explicitly talks about that. Everything you've just said talks to modernization. So you typically in financial services find a lot of relation. Database twenty-year-old, hardened, etcetera, high availability. Give them credit for that. But a lot of times you'll see them just shift that into the cloud. You guys chose not to do that. What was the modernization journey look like? >>So it's a bit of, um yeah, a firm believer in pragmatism and using. I think you touched on earlier the appropriate technology. So >>horses for courses >>exactly right out of my mouth. And I was talking to one of the uh, the investor analysts earlier. And you know, the exact same question comes up, right? So if you've got a relation database or you've got a big legacy system and you're not gonna mainframe or whatever it is and you wanna pull that over when you it's not just a case of moving the data model from one paradigm to another. You need to look at it holistically, and you need to be ambitious. I think the industry has got, you know, quite nervous about some of these transformation projects, but in some ways it might be counter intuitive. I think being ambitious and being in bold is a better way. Better way through, you know, take take of you, look at it holistically. Layout of plan. It is hard. It is hard to do these sorts of transformations, but that's what makes it the challenge. That's what makes it fun. Take take those bold steps. Look at it holistically. Look at the end state and then work out a practical way. You can deliver value to the business and your customers as you deliver on the road. So >>did you migrate from a traditional R D B. M s to go. >>So So, Yeah, this is a conversation. So, uh, in the late nineties, the kind of the phrase document model hasn't really been coined yet. And for some of our work at the time, we refer to as a hierarchical model. Um, And at that point in time, really, if you wanted to sell to a bank, you needed to be running Oracle. So we took this data model and we got it running an article and then other relational databases as well, but actually under the colors there it is, sort of as well. So there is a project that we're looking at to say Well, okay, taking that model, which is in a relational database. And of course, you build over time, you do rely on some of the features of relations databases moving that over to something like, isn't it? You know, it's not quite as simple as just changing the data model. Um, so there's a few bits and pieces that we need to work through, but there is a concept that we are running, which is looking really promising and spurred on by the amazing results from the benchmark. That could be something That's really >>yeah, I think you know, 20 years ago you probably wouldn't even thought about it. It's just too risky. But today, with the modern tools and the cloud and you're talking about micro services and containers, it becomes potentially more feasible. >>But the other side of it is, you know, it's only relatively recently the Mongo who's had transaction support across multiple document multi collection transactions and in banking. As we all know, you know, it's highly regulated. That is, all of your worst possible non functional requirement. Security transaction reality. Thomas City You know, the whole the whole shebang. Your worst possible nightmare is Monday morning for >>us. So and I think one part which is exciting about this Tony is a very good practical example about this large scale modernization and cutting out by cutting off that layer and going back to the hierarchical internal structures. We're simply find a lot of the backing components of our because obviously translation which was done before, it's not need it anymore. And that is as well for me, an exciting example to see how long it takes what it is. So Tony space in my life experiments so to speak >>well, you're right because it used to be those migrations. Where how many line of code? How long do I have to freeze it? And that a lot of times lead people to say, Well, forget it, because the business is going to shut down. >>But now we do that. We do that. So I'm working, obviously, besides the work with a lot of financial clients, and but now it's my job is normally shift and left a pain in the game because the result of the work is when they move everything to the cloud and it was bad before. It will not be better in the cloud only because it's in somebody else's data center. So these modernization and innovation factor is absolutely critical. And it's only said that people get it by now. This shift and left over it is how can I innovate? How can accelerate innovation, and that leads very quickly to the document model discussion. >>Yeah, I think the world practitioners will tell you, if you really want to affect the operational model, have a meaningful impact on your business. You have to really modernized. You can't just lift shift that they're absolutely. You know, what's the difference between hundreds of millions or billions in some cases, versus, you know, some nice little hits here or there. >>So we see as well a lot of clients asking for solutions like the terminal solutions. And like others where there is not anymore discussion about how to move to the The question is how fast how can accelerate. We see the services request the first one. It's amazing. After the event, what we had in London, 100 clients calling us. So it's not our sales people calling upon the clients, the clients coming in. I saw it. How do we get started? And that is for me, from the vendor perspective, so to speak. Amazing moment >>yourself. You go, guys, we're gonna go. Thanks so much for that. You have to have you back and see how that goes. That. Yeah, that's a big story of if you're a great All right, keep it right there. Everybody will be right back. This is David for the Cube. You're watching our live coverage of mongo D B World 20 twenty-two from New York City. >>Yeah, >>Yeah, yeah, yeah, yeah
SUMMARY :
Here is the c e o of those Disrupting the finance world. So we are a software And and so that's why I don't know if you consider that disruptive. of, um, buzzword jail where you could choose words to go into I mean, it's a fascinating piece that it could be truly transformative if we get it right, So, Boris, you have industry solutions in your title. And that's obviously the clients moving show several weeks ago in London and says, Boris, let's do a benchmark And maybe you bring your story So this was 200 million accounts, 100 million customers, So this is you know, So we have This is something we do in the lab you couldn't go live on. So this is not like let's define something new for the world. So it means you get these really efficient numbers what that helped us do with, All that stuff. When I talk to people, we have what we call a system So the the way we the way we architect the solution is it follows something and okay, and the workload had a high locality medium locality. we don't have that. so explain that That's not That's not the mindset for a document. In the document database, you don't have the hot spotting the one single field so that was very close to a So 100 and It's a real life environment out into the wild with the benchmark driving and driving. So all of the banks, when they take the latest release, is they get these benefits. and this was running in the cloud. So this was list, Um, 80 on a W s with a W s cases And then at least for the peace. the timing from, uh, the world. So we see a lot of good feedback as well when we bring it So you typically in financial I think you touched on earlier the appropriate technology. And you know, the exact same question comes up, So So, Yeah, this is a conversation. yeah, I think you know, 20 years ago you probably wouldn't even thought about it. But the other side of it is, you know, it's only relatively recently the the backing components of our because obviously translation which was done before, it's not need it anymore. And that a lot of times lead people to say, of financial clients, and but now it's my job is normally shift and left a pain in the what's the difference between hundreds of millions or billions in some cases, versus, you know, So we see as well a lot of clients asking for solutions like You have to have you back and see how that goes.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Boris | PERSON | 0.99+ |
Tony | PERSON | 0.99+ |
100,000 | QUANTITY | 0.99+ |
London | LOCATION | 0.99+ |
Tony Coleman | PERSON | 0.99+ |
100 | QUANTITY | 0.99+ |
20% | QUANTITY | 0.99+ |
Temenos | PERSON | 0.99+ |
41 | QUANTITY | 0.99+ |
100 clients | QUANTITY | 0.99+ |
one quarter | QUANTITY | 0.99+ |
New York City | LOCATION | 0.99+ |
Boris Bialek | PERSON | 0.99+ |
99% | QUANTITY | 0.99+ |
tomorrow | DATE | 0.99+ |
three years | QUANTITY | 0.99+ |
Monday morning | DATE | 0.99+ |
One-millisecond | QUANTITY | 0.99+ |
100 million customers | QUANTITY | 0.99+ |
89 environments | QUANTITY | 0.99+ |
thirty-two | QUANTITY | 0.99+ |
this year | DATE | 0.99+ |
100,000 transactions | QUANTITY | 0.99+ |
Mongo | ORGANIZATION | 0.99+ |
hundreds of millions | QUANTITY | 0.99+ |
102,800 seventy-five transactions | QUANTITY | 0.99+ |
second | QUANTITY | 0.99+ |
Michael Services | ORGANIZATION | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
First time | QUANTITY | 0.98+ |
billions | QUANTITY | 0.98+ |
three-quarters | QUANTITY | 0.98+ |
20 years ago | DATE | 0.98+ |
first one | QUANTITY | 0.98+ |
several weeks ago | DATE | 0.98+ |
Twenty-five 1000 transactions | QUANTITY | 0.98+ |
late nineties | DATE | 0.98+ |
80 | QUANTITY | 0.98+ |
David | PERSON | 0.98+ |
over 3000 financial institutions | QUANTITY | 0.98+ |
three years ago | DATE | 0.98+ |
MongoDB | ORGANIZATION | 0.98+ |
over 1.2 billion people | QUANTITY | 0.97+ |
Today | DATE | 0.97+ |
today | DATE | 0.97+ |
one | QUANTITY | 0.97+ |
200 million accounts | QUANTITY | 0.96+ |
Seventy-five 1000 queries | QUANTITY | 0.96+ |
Seventy-five 1000 transactions | QUANTITY | 0.96+ |
one thing | QUANTITY | 0.95+ |
15 years | QUANTITY | 0.95+ |
about Twenty-five 1000 transactions | QUANTITY | 0.95+ |
this morning | DATE | 0.94+ |
few weeks ago | DATE | 0.94+ |
one paradigm | QUANTITY | 0.94+ |
twenty-year-old | QUANTITY | 0.93+ |
one part | QUANTITY | 0.93+ |
second response | QUANTITY | 0.93+ |
Thomas City | PERSON | 0.93+ |
more | QUANTITY | 0.92+ |
one single field | QUANTITY | 0.92+ |
10, 15 years | QUANTITY | 0.92+ |
10,000 transactions a second | QUANTITY | 0.92+ |
50 banks | QUANTITY | 0.92+ |
Michael | PERSON | 0.92+ |
first | QUANTITY | 0.91+ |
first live event | QUANTITY | 0.9+ |
mongo D B World 20 twenty-two | TITLE | 0.9+ |
six weeks | DATE | 0.9+ |
Infinity services | ORGANIZATION | 0.83+ |
20 twenty-two | QUANTITY | 0.83+ |
single single 80 system | QUANTITY | 0.8+ |
Atlas | ORGANIZATION | 0.8+ |
50 | QUANTITY | 0.75+ |
four times | QUANTITY | 0.72+ |
for years | QUANTITY | 0.68+ |
a second | QUANTITY | 0.63+ |
every two | QUANTITY | 0.61+ |
double | QUANTITY | 0.59+ |
up | QUANTITY | 0.57+ |
3 3 Adminstering Analytics v4 TRT 20m 23s
>>Yeah. >>All right. Welcome back to our third session, which is all about administering analytics at Global Scale. We're gonna be discussing how you can implement security data compliance and governance across the globe at for large numbers of users to ensure thoughts. What is open for everyone across your organization? So coming right up is Cheryl Zang, who is a senior director of product management of Thought spot, and Kendrick. He threw the sports sports director of Systems Engineering. So, Cheryl and Kendrick, the floor is yours. >>Thank you, Tina, for the introduction. So let's talk about analytics scale on. Let's understand what that is. It's really three components. It's the access to not only data but its technology, and we start looking at the intersection of that is the value that you get as an organization. When you start thinking about analytics scale, a lot of times we think of analysts at scale and we look at the cloud as the A seven m for it, and that's a That's an accurate statement because people are moving towards the cloud for a variety of reasons. And if you think about what's been driving, it has been the applications like Salesforce, Forcados, Mongo, DB, among others. And it's actually part of where we're seeing our market go where 64% of the company's air planning to move their analytics to the cloud. And if you think of stock spotted specifically, we see that vast majority of our customers are already in the cloud with one of the Big Four Cloud Data warehouses, or they're evaluated. And what we found, though, is that even though companies are moving their analytics to the cloud, we have not solved. The problem of accessing the data is a matter of fact. Our customers. They're telling us that 10 to 25% of that data warehouse that they're leveraging, they've moved and I'm utilizing. And if you look at in General, Forrester says that 60 to 73% of data that you have is not being leveraged, and if we think about why you go through, you have this process of taking enterprise data, moving it into these cubes and aggregates and building these reports dashboards. And there's this bottleneck typically of that be I to and at the end of the day, the people that are getting that data on the right hand side or on Lee. Anywhere from 20 to 30% of the population when companies want to be data driven is 20 to 30% of the population. Really what you're looking for now it's something north of that. And if you think of Cloud data, warehouse is being the the process and you bring Cloud Data Warehouse and it's still within the same framework. You know? Why invest? Why invest and truly not fix the problem? And if you take that out and your leverage okay, you don't necessarily have the You could go directly against the warehouse, but you're still not solving the reports and dashboards. Why investing truly not scale? It's the three pillars. It's technology, it's data, and it's a accessibility. So if we look at analytics at scale, it truly is being able to get to that north of the 20 to 30% have that be I team become enablers, often organization. Have them be ableto work with the data in the Cloud Data warehouse and allow the cells marking finding supplies and then hr get direct access to that. Ask their own questions to be able to leverage that to be able to do that. You really have to look at your modern data architecture and figure out where you are in this maturity, and then they'll be able to build that out. So you look at this from the left to right and sources. It's ingestion transformation. It's the storage that the technology brains e. It's the data from a historical predictive perspective. And then it's the accessibility. So it's technology. It's data accessibility. And how do you build that? Well, if you look at for a thought to spot perspective, it truly is taking and driving and leveraging the cloud data warehouse architectures, interrogated, essay behind it. And then the accessibility is the search answers pen boards and embedded analytics. If you take that and extend it where you want to augment it, it's adding our partners from E T L R E L t. Perspective like al tricks talent Matile Ian Streaming data from data brings or if you wanna leverage your cloud, data warehouses of Data Lake and then leverage the Martin capability of your child data warehouse. The augmentation leveraging out through its data bricks and data robot. And that's where your data side of that pillar gets stronger, the technologies are enabling it. And then the accessibility from the output. This thought spot. Now, if you look at the hot spots, why and how do we make this technology accessible? What's the user experience we are? We allow an organization to go from 20 to 30% population, having access to data to what it means to be truly data driven by our users. That user experience is enabled by our ability to lead a person through the search process. There are search index and rankings. This is built for search for corporate data on top of the Cloud Data Warehouse. On top of the data that you need to be able to allow a person who doesn't understand analytics to get access to the data and the questions they need to answer, Arcuri Engine makes it simple for customers to take. Ask those questions and what you might think are not complex business questions. But they turn into complex queries in the back end that someone who typically needs to know that's that power user needs to know are very engine. Isolate that from an end user and allows them to ask that question and drive that query. And it's built on an architecture that allows us to change and adapt to the types of things. It's micro services architecture, that we've not only gone from a non grim system to our cloud offering, in a matter of of really true these 23 years. And it's amazing the reason why we can do that, do that and in a sense, future proof your investment. It's because of the way we've developed this. It's wild. First, it's Michael Services. It's able to drive. So what this architecture ER that we've talked about. We've seen different conversations of beyond its thought spot everywhere, which allows us to take that spot. One. Our ability to for search for search data for auto analyzed the Monitor with that govern security in the background and being able to leverage that not only internally but externally and then being able to take thought spot modeling language for that analysts and that person who just really good at creating and let them create these models that it could be deployed anywhere very, very quickly and then taking advantage off the Cloud Data warehouse or the technology that you have and really give you accessibility the technology that you need as well as the data that you need. That's what you need to be able to administer, uh, to take analytics at scale. So what I'm gonna do now is I'm gonna turn it over to Cheryl and she's gonna talk about administration in thought spot. Cheryl, >>thank you very much Can take. Today. I'm going to show you how you can administrator and manage South Spot for your organization >>covering >>streaming topics, the user management >>data management and >>also user adoption and performance monitoring. Let's jump into the demo. >>I think the Southport Application The Admin Council provides all the core functions needed for system level administration. Let's start with user management and authentication. With the user tab. You can add or delete a user, or you can modify the setting for an existing user. For example, user name, password email. Or you can add the user toe a different group with the group's tab. You can add or delete group, or you can manage the group setting. For example, Privileges associated with all the group members, for example, can administrate a soft spot can share data with all users or can manage data this can manage data privilege is very important. It grants a user the privileges to add data source added table and worksheet, manage data for different organizations or use cases without being an at me. There is also a field called Default Pin Board. You can select a set of PIN board that will be shown toe all of the users in that group on their homepage in terms off authentication. Currently, we support three different methods local active directory and samel By default. Local authentication is enabled and you can also choose to have several integration with an external identity provider. Currently, we support actor Ping Identity, Seaside Minor or a T. F. S. The third method is integration with active directory. You can configure integration with L DAP through active directory, allowing you to authenticate users against an elder up server. Once the users and groups are added to the system, we can share pin board wisdom or they can search to ask and answer their own questions. To create a searchable data, we first need to connect to our data warehouses with embraced. You can directly query the data as it exists in the data warehouse without having to move or transfer the data. In this page, you can add a connection to any off the six supported data warehouses. Today we will be focusing on the administrative aspect off the data management. So I will close the tap here and we will be using the connections that are already being set up. Under the Data Objects tab, we can see all of the tables from the connections. Sometimes there are a lot of tables, and it may be overwhelming for the administrator to manage the data as a best practice. We recommend using stickers toe organize your data sets here, we're going to select the Salesforce sticker. This will refined a list off tables coming from Salesforce only. This helps with data, lineage and the traceability because worksheets are curated data that's based on those tables. Let's take a look at this worksheet. Here we can see the joints between tables that created a schema. Once the data analyst created the table and worksheet, the data is searchable by end users. Let's go to search first, let's select the data source here. We can see all of the data that we have been granted access to see Let's choose the Salesforce sticker and we will see all of the tables and work ship that's available to us as a data source. Let's choose this worksheet as a data source. Now we're ready to search the search Insight can be saved either into a PIN board or an answer. Okay, it's important to know that the sticker actually persist with PIN board and answers. So when the user logging, they will be able to see all of the content that's available to them. Let's go to the Admin Council and check out the User Adoption Pin board. The User Adoption Pin board contains essential information about your soft spot users and their adoption off the platform. Here, you can see daily active user, weekly, active user and monthly active user. Count that in the last 30 days you can also see the total count off the pin board and answers that saved in the system. Here, you can see that unique count off users. Now. You can also find out the top 10 users in the last 30 days. The top 10 PIN board consumers and top 10 ad hoc searchers here, you can see that trending off weekly, active users, daily, active users and hourly active users over time. You can also get information about popular pin boards and user actions in the last one month. Now let's zoom in into this chart. With this chart, you can see weekly active users and how they're using soft spot. In this example, you can see 60% of the time people are doing at Hawk search. If you would like to see what people are searching, you can do a simple drill down on quarry tax. Here we can find out the most popular credit tax that's being used is number off the opportunities. At last, I would like to show you assistant performance Tracking PIN board that's available to the ad means this PIN board contains essential information about your soft spot. Instance performance You this pimple. To understand the query, Leighton see user traffic, how users are interacting with soft spot, most frequently loaded tables and so on. The last component toe scowling hundreds of users, is a great on boarding experience. A new feature we call Search Assist helps automate on boarding while ensuring new users have the foundation. They need to be successful on Day one, when new users logging for the first time, they're presented with personalized sample searches that are specific to their data set. In this example, someone in a sales organization would see questions like What were sales by product? Type in 2020. From there are guided step by step process helps introduce new users with search ensuring a successful on boarding experience. The search assist. The coach is a customized in product Walk through that uses your own data and your own business vocabulary to take your business users from unfamiliar to near fluent in minutes. Instead of showing the entire end user experience today, I will focus on the set up and administration side off the search assist. Search Assist is easy to set up at worksheet level with flexible options for multiple guided lessons. Using preview template, we help you create multiple learning path based on department or based on your business. Users needs to set up a learning path. You're simply feeling the template with relevant search examples while previewing what the end user will see and then increase the complexity with each additional question toe. Help your users progress >>in summary. It is easy to administrator user management, data management, management and the user adoption at scale Using soft spot Admin Council Back to you, Kendrick. >>Thank you, Cheryl. That was great. Appreciate the demo there. It's awesome. It's real life data, real life software. You know what? Enclosing here? I want to talk a little bit about what we've seen out in the marketplace and some of them when we're talking through prospects and customers, what they talk a little bit about. Well, I'm not quite area either. My data is not ready or I've got I don't have a file data warehouse. That's this process. In this thinking on, we have examples and three different examples. We have a company that actually had never I hadn't even thought about analytics at scale. We come in, we talked to them in less than a week. They're able to move their data thought spot and ask questions of the billion rose in less than a week now. We've also had customers that are early adoption. They're sticking their toes in the water around the technology, so they have a lot of data warehouse and they put some data at it, and with 11 minute within 11 minutes, we were able to search on a billion rows of their data. Now they're adding more data to combine to, to be able to work with. And then we have customers that are more mature in their process. Uh, they put large volumes of data within nine minutes. We're asking questions of their data, their business users air understanding. What's going on? A second question we get sometimes is my data is not clean. We'll talk Spot is very, very good at finding that type of data. If you take, you start moving and becomes an inner door process, and we can help with that again. Within a week, we could take data, get it into your system, start asking business questions of that and be ready to go. You know, I'm gonna turn it back to you and thank you for your time. >>Kendrick and Carol thank you for joining us today and bringing all of that amazing inside for our audience at home. Let's do a couple of stretches and then join us in a few minutes for our last session of the track. Insides for all about how Canadian Tire is delivering Korean making business outcomes would certainly not in a I. So you're there
SUMMARY :
We're gonna be discussing how you can implement security data compliance and governance across the globe Forrester says that 60 to 73% of data that you have is not I'm going to show you how you Let's jump into the demo. and it may be overwhelming for the administrator to manage the data as data management, management and the user adoption at scale Using soft spot Admin and thank you for your time. Kendrick and Carol thank you for joining us today and bringing all of that amazing inside for our audience at home.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Cheryl | PERSON | 0.99+ |
Tina | PERSON | 0.99+ |
Kendrick | PERSON | 0.99+ |
Cheryl Zang | PERSON | 0.99+ |
10 | QUANTITY | 0.99+ |
60 | QUANTITY | 0.99+ |
20 | QUANTITY | 0.99+ |
60% | QUANTITY | 0.99+ |
Forrester | ORGANIZATION | 0.99+ |
third session | QUANTITY | 0.99+ |
64% | QUANTITY | 0.99+ |
11 minute | QUANTITY | 0.99+ |
Today | DATE | 0.99+ |
First | QUANTITY | 0.99+ |
30% | QUANTITY | 0.99+ |
nine minutes | QUANTITY | 0.99+ |
third method | QUANTITY | 0.99+ |
second question | QUANTITY | 0.99+ |
Global Scale | ORGANIZATION | 0.99+ |
first time | QUANTITY | 0.99+ |
South Spot | ORGANIZATION | 0.99+ |
less than a week | QUANTITY | 0.99+ |
23 years | QUANTITY | 0.99+ |
2020 | DATE | 0.99+ |
Carol | PERSON | 0.99+ |
Leighton | ORGANIZATION | 0.98+ |
today | DATE | 0.98+ |
Michael Services | ORGANIZATION | 0.98+ |
25% | QUANTITY | 0.97+ |
73% | QUANTITY | 0.97+ |
hundreds of users | QUANTITY | 0.97+ |
11 minutes | QUANTITY | 0.97+ |
Matile Ian | PERSON | 0.97+ |
first | QUANTITY | 0.96+ |
three pillars | QUANTITY | 0.96+ |
three components | QUANTITY | 0.96+ |
one | QUANTITY | 0.95+ |
three different methods | QUANTITY | 0.95+ |
10 users | QUANTITY | 0.95+ |
Day one | QUANTITY | 0.95+ |
six supported data warehouses | QUANTITY | 0.94+ |
Systems Engineering | ORGANIZATION | 0.94+ |
Thought spot | ORGANIZATION | 0.93+ |
Data Lake | ORGANIZATION | 0.91+ |
Arcuri Engine | ORGANIZATION | 0.9+ |
10 ad hoc searchers | QUANTITY | 0.9+ |
Warehouse | TITLE | 0.89+ |
billion rows | QUANTITY | 0.88+ |
Cloud Data warehouse | TITLE | 0.87+ |
billion | QUANTITY | 0.86+ |
three different examples | QUANTITY | 0.86+ |
last one month | DATE | 0.86+ |
Salesforce | ORGANIZATION | 0.86+ |
a week | QUANTITY | 0.85+ |
Canadian | OTHER | 0.84+ |
each additional question | QUANTITY | 0.83+ |
v4 | OTHER | 0.83+ |
last 30 days | DATE | 0.78+ |
Salesforce | TITLE | 0.77+ |
last 30 days | DATE | 0.77+ |
Korean | OTHER | 0.75+ |
One | QUANTITY | 0.74+ |
Search | TITLE | 0.73+ |
Big Four | QUANTITY | 0.73+ |
Martin | PERSON | 0.72+ |
DB | TITLE | 0.72+ |
10 PIN | QUANTITY | 0.71+ |
Southport | TITLE | 0.66+ |
Lee | PERSON | 0.66+ |
Hawk | ORGANIZATION | 0.66+ |
Adminstering Analytics | TITLE | 0.66+ |
Mongo | TITLE | 0.64+ |
Forcados | TITLE | 0.64+ |
Seaside Minor | ORGANIZATION | 0.62+ |
gress | ORGANIZATION | 0.6+ |
Cloud | TITLE | 0.57+ |
Ping | TITLE | 0.53+ |
seven | QUANTITY | 0.49+ |
User Adoption | ORGANIZATION | 0.39+ |
20m | OTHER | 0.36+ |
User | ORGANIZATION | 0.35+ |
Adoption | COMMERCIAL_ITEM | 0.35+ |