4.03 Mastering End-To-End KQL Transformations In Microsoft Fabric

   • Microsoft Fabric For Beginners  
In this tutorial, I explore KQL processing capabilities in Microsoft Fabric.
I explain basic KQL operators and commands and demonstrate their usage.
I also explain different tools to automate data movement and transformations within KQL database and demonstrate usage of table update, cache and retention policies.
Furthermore I show how to use Spark notebooks and Data Pipelines to orchestrate KQL transformations.
Finally, I demonstrate visualization options, like render operators and Power BI dashboards to consume KQL data.
You can download demo script from here: https://github.com/fazizov/youtube/bl...

Chapters:
00:00- Introduction
01:18- Preview
04:21- Demo-Querysets
08:48- Basic column-level KQL operators
12:09- Aggregate operators
12:47- Join operators
13:29- Table management commands
14:20- Table write commands
15:16- Multi-step transformations-let operator
16:49- KQL Functions
17:55- Overview of data movement and transformation automation options-Data Pipelines, Spark Notebooks, Table Update Policies
21:17- What is table update policy?
24:41- Demo- using data pipelines to orchestrate KQL transformations
26:22- Materialized views
27:54- Referring to KQL tables from Spark notebooks
30:15- Cache and Retention policies
30:50- Table update policies
32:23- Building end-to-end streaming pipelines in KQL
36:35- Dimensional transformations
43:42- Materialized views
44:50- KQL visualizations-render operator
45:49- Power BI visualizations in KQL

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Official Documentation:
https://learn.microsoft.com/en-us/fab...
https://learn.microsoft.com/en-us/fab...
https://learn.microsoft.com/en-us/azu...
https://learn.microsoft.com/en-us/str...
https://learn.microsoft.com/en-us/azu...

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