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How to Create Operational Analytics with Window Functions in Azure SQL - Part 3 | Data Exposed


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Running complex aggregations and analytical functions on real-time operational databases is a powerful capability in Azure SQL. In the last part of this three-part series with Silvano Coriani, we will see how Window Functions can be a great tool to express analytical calculations on real-time data sets. [01:30]​ Operational Analytics: what kind of analytics?[03:12]​ A Common Business Scenario[05:10]​ Old school[06:22]​ Performance with self-join and subqueries[06:42]​ New school[08:01]​ Performance with Window Functions[08:50]​ Demo: Performance with Window Functions[13:18]​ Window Functions capabilities[14:54]​ Getting started More episodes in this Operational Analytics Series:How Azure SQL Enables Real-time Operational Analytics (HTAP) - Part 1Optimize Existing Databases amp; Apps with Operational Analytics in Azure SQL - Part 2 Resources:Get started with Columnstore for real-time operational analyticsSample performance with Operational Analytics in WideWorldImportersT-SQL Window Functions: For data analysis and beyond, 2nd EditionReal-Time Operational Analytics:Memory-Optimized Tables and Columnstore IndexDML operations and nonclustered columnstore index (NCCI) in SQL Server 2016Filtered nonclustered columnstore index (NCCI)
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