Live Demo: Oracle Autonomous Data Warehouse Cloud

hi good afternoon I wanted to show you a quick demo so you can actually see what the autonomous data warehouse cloud looks like well I'm going to show you in this demo I'm gonna highlight three areas I'm first going to show you how quick and easy it is to provision a new database from 0 and so you can see when a thomas database really looks like from a provisioning standpoint and then i'm going to talk about the scalability and the elasticity of it I'll show you how easy and quick it is to scale and then finally I'm going to show you how you integrate this service with Oracle analytics cloud which is what business users would actually use that's how they would interact with the data warehouse so let's start here we're going to start I'm going to go to cloud Oracle calm and I'm going to sign in to my cloud account this is a product manager I have my autonomous data warehouse 4 p.m. account and I will log in and this is exactly what a customer is going to be seeing the first time they come in to their Oracle cloud account you're going to be coming into the cloud dashboard where you're going to see a set of products and you can choose which products you want to use we're going to be looking at the autonomous data warehouse cloud I'm gonna open the service console so right now I don't have any databases created I don't have any data warehouses I have the option here I can look at a tutorial I can look at some instructions we're just gonna step ahead to create a new database and so I'm gonna create an example database and when you look at this screen I only have to do four things to create a database I'm typing the database name I'm typing a number of CPUs and then typing the the storage capacity and then the administrator password now we should pause for a second and think about this because sometimes when you see something you know if you look at this you say okay that makes sense you gotta name the database and we need to say the size of the database we're creating and all this is very logical this is what you would need to do when you create a new data warehouse but when you see something simple sometimes you don't realize all the things that are happening under the cover there are a lot of decisions in a law of complexity that's being done for you by the autonomous data warehouse cloud there's no questions here about what type of hardware we should use there's no question about do we want to use spinning disk or flash drives there's nothing about how do you want to configure your backup there's nothing about how do you setup the database well it's the you know for those of you who use Oracle a lot or a DBA you know what's you're in it or for this database what's your initialization parameters you don't have to make any of these decisions because this is what an autonomous database is Oracle is choosing an optimal database configuration for data warehousing this is what we built this is the intelligence that we built into our cloud with the autonomous database so now I'm going to quickly confirm my settings and create the database you can see we've started to create the service here and what we're doing is we're going off and we are provisioning a new database a new data warehouse and this is going to be an enterprise ready database we're provisioning this with all the proper setup for security it's going to be fully encrypted the system is a highly available infrastructure has clustered database technology and redundant storage we're provisioning this on top of Exadata for high performance so we're really assembling all the components together to build a true enterprise database for enterprise deployments right so when we look here they refresh the screen they're going to say it's still creating you know perfection takes time sometimes right we need to make sure we get everything right and when this comes back we're going to have a database that's ready for you to load data ready for you to run queries right away off the bat so we can see it's created now and once you think about that as well right because we created this database and probably about 60 seconds about 40 to 60 seconds it would take the same length of time if we created a database it was 40 CPUs in setup 4 CPUs when Oracle is really built here is a true database cloud we're provisioning new databases at the speed that other clouds might provision a VM and we're provisioning databases that are fully enterprise ready and able to go so if we look at this console we can see that we can manage various aspects of the database we can start the service stop the service we could scale the database up and down so we quickly seen how we provision a new database how we create a database now I'm going to turn and talk about how the business users are reduced to database so we're going to look at Oracle analytics cloud so we're going to start with the sort of homepage work on in legs cloud Oracle and legs cloud is a comprehensive set of tools for enterprise business intelligence and self-service analytics this is the type of tool that the actual business analysts would use to access the data in Oracle's autonomous data warehouse so this is another cloud service that's part of Oracle's platform as a service family of products and what I've done here is I've actually gone in and created a project already specifically to show you how you can use AAC against New York a database so we're gonna sit and select this project down here and we're going to come in and first of all we're gonna start and just briefly look at the data that we have in the database I'm not showing you data loading right now in this demonstration but what we are going to do is we're going to run queries I get it's a sample schema that's already built into this database so the database I just created you could go in and run these queries and these dashboards right now and you can see that we have a schema that has actually quite a bit of data it has the largest table has six billion rows you can see some of the data characteristics that we have in here you know just simple data distribution it's tracking sales across multiple industries and across multiple geographies and so here we have a very simple visualization we look at product by product brand and regions so this is the type of analysis of the business user might see and I've added a couple other technical things on this screen just for the purposes to show you how Thomas data warehouse cloud worked you can see the sequel that's actually going to the database and I pre-populated this report and we can see that when we went to this database and ran with four CPUs populating this report took about 33 seconds now keep in mind that this was over 6 billion rows and so 33 seconds is pretty good performance but if you look down here in the lower and the lower right we've actually built a custom visualization and it's set up so that you can scale the autonomous data warehouse cloud database there's a couple of ways you can scale the database one way is using the service console that you just saw but you can also scale the database using a REST API and that's what we're doing here Oracle Analects cloud is going to call the REST API so we can see we could scale to sort of any number of CPUs that we would want to be scaling to you know we could scale up in this case we just set the slider bar to 128 but you could scale up to even larger number of CPUs what I'm going to do now is I'm going to scale the database to 16 all right and so we're gonna scale this database up to 16 CPUs now this occurs fully online and without any interruption of the users who are rain on the system today and this is a big deal this is very different than how other databases work and this is really the the instantiation of very sophisticated database technology so we are sizing the system up from 4 to 16 CPUs anyone who's on this data warehouse running queries their queries continue to run uninterrupted all the workloads continue to run and what's going to happen now as I submit a new query now that I've resized the database I'm going to refresh the data now the new query is going to be running with the larger amount of resource and now instead of 4 CPUs it's going to be running with 16 CPUs and we could see that this query took about 8 seconds to run and so but just by scaling up from 4 to 16 CPUs you have your hands on the performance of the system the way that you're going to increase performance is by scaling CPUs you can do it anytime and as Larry mentioned earlier write your workload increases end of a corner processing increase the number of CPUs your workloads down you can decrease the number of CPUs this elasticity enables you to save money so now we're going to turn to and look at a more typical sort of screen that a business analyst might want to see we have four visualizations here we can see we have a map visualization a donut chart and all of these are fully interactive so we highlight sections of the map highlight a Quadra of the donut chart we see the map being highlighted we can go in and we can add new types of analytics on these charts as well for example in this bar chart if I right click I can specify that I want to add a trendline and we can dynamically add this type of result onto the analytic onto the onto this graph again you can see that you're able to choose subsets of data potentially drill into the data and these are the type of things that business users going to be doing and all this is running against our very large data set so I wanted to show you one other very quick example of using work on lakes cloud you can see that you might have a variety of projects the data sets but I wanted to talk about a pretty nifty feature where'd you just suppose you just start typing in your query you say I want to look at sales by product and then I want to look at the profit by customer segment so you're just typing in an English query or an ellipse cloud is going to recommend visualizations based upon your query you can choose visualizations these are fully interactive just as before so you could choose a subset of data right here look at the graph and so you get the feel for how business users would use it I want to show you one last thing before we leave this demo we're going to come back and look at our original visualization and let's suppose that we are done using our database for today let's suppose that we're going to not be using this data warehouse until tomorrow morning well the elasticity of our system enables us to shut down our CPUs we could shut off the CPU shut the CPUs to zero and what happens here is now you're not paying for the CPU so you continue to pay for your storage of your database but you save money by not having to pay for your CPUs so what I done in this quick demo is what I tried to highlight are really three quick things first I've shown how the database how of the autonomous data warehouse cloud is autonomous I've shown how easy it is to provision and create a new data warehouse how users don't need to know all the details and underpinnings of the of the system in order to create this data warehouse I wasn't able to show it here but users don't have to do anything for ongoing maintenance they don't have to do backups of the database they don't have to gather statistics so all of these continuous online operational aspects are completely autonomous with this service second I've shown the elasticity I've shown how you can increase and decrease the CPUs to get the performance and scalability that you need and I've shown how you can shut the CPUs off to save money elasticity enables you to pay for exactly to want to use and because Oracle's elasticity is fully online you can change at any time you can really maximize your cost savings and then third I've shown how this is integrated with all other Oracle cloud services we saw some visualizations with Oracle analytics cloud so we're really excited about this new product it has a lot of revolutionary new cloud capabilities and we really think this represents the next generation of databases with our autonomous database family thank you [Applause] you

Channel: Oracle

Views: 24,959

Keywords: larry ellison, fy17, Autonomous Database, autonomous data warehouse, self-driving, artificial intelligence, Autonomous, self-repairing, George Lumpkin, database, oracle autonomous database, AI, retire-2018, database cloud, oracle autonomous, larry, 30530185, oracle autonomous data warehouse, yt, oracle autonomous database cloud, oracle AI, fy18, autonomous database cloud, Database, EXT-18-83, data warehouse, autonomous database

Id: XkOdlIewqLc

Length: 14min 10sec (850 seconds)

Published: Wed Mar 28 2018