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.
0:00 Introduction
1:30 Operational Analytics: what kind of analytics?
3:12 A Common Business Scenario
5:10 Old school
6:22 Performance with self-join and subqueries
6:42 New school
8:01 Performance with Window Functions
8:50 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 1: • How Azure SQL Enables Real-time Opera...
How to Optimize Existing Databases & Applications with Operational Analytics in Azure SQL - Part 2: • Optimize Existing Databases & Apps wi...
How to Create Operational Analytics with Window Functions in Azure SQL - Part 3: • How to Create Operational Analytics w...
✔️ Resources:
Get started with Columnstore for real-time operational analytics:
https://docs.microsoft.com/en-us/sql/...
Sample performance with Operational Analytics in WideWorldImporters:
https://github.com/microsoft/sql-serv...
T-SQL Window Functions: For data analysis and beyond, 2nd Edition:
https://www.microsoftpressstore.com/s...
Real-Time Operational Analytics:
https://docs.microsoft.com/en-us/arch...
https://docs.microsoft.com/en-us/arch...
https://docs.microsoft.com/en-us/arch...
📌 Let's connect:
Twitter: Silvano Coriani, / scoriani
Twitter: Anna Hoffman, / analyticanna
Twitter: AzureSQL, https://aka.ms/azuresqltw
🔴 To check out even more Data Exposed episodes, see our playlist: https://aka.ms/dataexposedyt
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#OperationalAnalytics #HTAP #AzureSQL
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