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)