Empowering Lakehouse Users – Data Engineering with Fabric
Learn how to use the OneLake Explorer and Data Wrangler extension in VS Code to empower users to work with data in Microsoft Fabric.
2024-05-22
1,819 reads
John F. Miner III
Combining Silver Tables into a Model – Data Engineering with Fabric
This next article in the series creates objects at the gold layer for consumption by combining tables from the silver layer of the lake house.
2024-05-15
3,453 reads
Metadata Driven Pipelines – Data Engineering with Fabric
This article explains metadata driven pipelines and shows an example in Microsoft Fabric.
2024-05-01
5,011 reads
Full vs. Incremental Loads – Data Engineering with Fabric
Learn how to perform full and incremental loads in Fabric with a little SparkSQL.
2024-04-17
6,562 reads
Managing Files and Folders with Python – Data Engineering with Fabric
In this article, learn how you can manage files and folders for both full and incremental loading situations.
2024-03-27
3,698 reads
Managed Vs Unmanaged Tables – Data Engineering with Fabric
Learn how to get started with Microsoft Fabric along with the differences between managed and unmanaged tables.
2024-03-20
4,762 reads
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Remotely Engineer Fabric Lakehouse objects: The Fabric Modern Data Platform
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Creating JSON III
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Testing is Becoming More Important
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Question of the Day
Creating JSON III
In a SQL Server 2025 table, called Beer, I have this data:
BeerIDBeerName 1Becks 2Fat Tire 3Mac n Jacks 4Alaskan Amber 8KirinI run this code:
SELECT JSON_OBJECTAGG(
BeerID: BeerName )
FROM beer;
What are the results? See possible answers