>>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