Create Raw Zone Tables using Generative AI: The Fabric Modern Data Platform
In this first article on the Fabric Modern Data Platform, we look at how to use Generative AI to build tables.
2025-04-07 (first published: 2025-04-02)
3,298 reads
Microsoft Fabric (Azure Synapse, Data Engineering, etc.)
Fabric Analytics for SQL folks: Part 1 - Fabric demystified
Unlock new opportunities for data-driven decision-making by grasping the significance of SQL and structured data in current data and analytics ecosystems like Microsoft Fabric.
2025-03-21
6,538 reads
Why use Tally Tables in the Fabric Warehouse? Data Engineering in Fabric
This next article in the Data Engineering with Fabric series showcases how tally tables can help load data in a Fabric warehouse.
2025-02-26
2,289 reads
How to Develop Solutions with Fabric Data Warehouse: Data Engineering with Fabric
In this next article in the Data Engineering with Fabric series, learn the different ways to develop schemas inside of Fabric.
2025-02-12
2,290 reads
An Effective Approach for High Volume Data in Azure Synapse
Learn about how you can efficiently load data in Azure Synapse.
2025-03-06 (first published: 2025-02-03)
1,220 reads
Partitioning Data in Microsoft Fabric to Improve Performance for Lakehouses, Warehouses, and Pipelines
Learn how to implement data partitioning within Microsoft Fabric to improve performance for Lakehouses, Warehouses, and Pipelines.
2025-01-13
How to Load a Fabric Warehouse: Data Engineering with Fabric
In this next level, learn how you can load data from Amazon S3 in Fabric.
2025-01-08
4,673 reads
Convert Excel Workbooks to CSV with Microsoft Fabric
For my new mission, I set out to convert a list of files from Excel to comma-separated values (CSV). We upload the original Excel files to a Data Lake in Fabric. We then need to convert a specific worksheet and move the CSV files to a different folder in Data Lake.
2024-12-25
Level 4 of the Stairway to Synapse Analytics: Create and Use a Delta Lake
Introduction In Level 1 of this series, I discussed Synapse Analytics basics and the steps for creating the Synapse Workspace. In Level 2, we analyzed Data Lake files using the Serverless SQL Pool. In Level 3, we analyzed Data Lake files using the Spark Pool. In Levels 4 and level 5, I will discuss the Delta […]
2025-06-06 (first published: 2024-12-18)
1,890 reads
Virtualizing GCP data by using Fabric Shortcuts: Data Engineering with Fabric
In the next installment of this series, learn how you can read data from the Google Cloud Platform (GCP) and virtualize it into your Azure Data Lake Storage.
2024-12-11
2,660 reads
Blogs
Why your data still can’t answer a simple question
Every organization I talk to has the same problem dressed up in different clothes....
T-SQL Tuesday #197 Invitation – An impactful session or two from a conference
By DataOnWheels
I am delighted to host this month’s T-SQL Tuesday invitation. If you are new...
Did You Really Name That Default?
By alevyinroc
Ten years (and a couple jobs) ago, I wrote about naming default constraints to...
Forums
The day-to-day pressures of a DBA team, and how we can work smarter with automation and AI
Comments posted to this topic are about the item The day-to-day pressures of a...
Using OPENJSON
Comments posted to this topic are about the item Using OPENJSON
Data Modeling with dbt for Visual Code: The Fabric Modern Data Platform
Comments posted to this topic are about the item Data Modeling with dbt for...
Question of the Day
Using OPENJSON
I have some data in a table that looks like this:
BeerID BeerName brewer beerdescription 1 Becks Interbrew Beck's is a German-style pilsner beer 2 Fat Tire New Belgium Toasty malt, gentle sweetness, flash of fresh hop bitterness. 3 Mac n Jacks Mac & Jack's Brewery This beer erupts with a floral, hoppy taste 4 Alaskan Amber Alaskan Brewing Alaskan Brewing Amber Ale is an "alt" style beer 8 Kirin Kirin Brewing Kirin Ichiban is a Lager-type beerIf I run this, what is returned?
select t1.key
from openjson((select t.* FROM Beer AS t for json path)) t1 See possible answers