Delta Table Performance Is Governed By Transaction Size: Data Engineering with Fabric
This next article examines the impact of transaction sizes on the performance of our Delta Parquet tables.
2024-09-11
2,210 reads
Microsoft Fabric (Azure Synapse, Data Engineering, etc.)
2024-09-06
335 reads
Microsoft Fabric: Using Lakehouse data in Real Time Dashboards
Real-Time dashboards are a great feature in Real Time Intelligence experience to monitor our data. However, by default ...
2024-08-30
2024-08-30
279 reads
Microsoft Fabric Warehouse Security: Object-Level, Column-Level and Row-Level
Learn about object-level, column-level, and row-level security in Microsoft Fabric Warehouse and how this can be implemented to limit access to data.
2024-08-28
A New and Improved Data Warehouse: Data Engineering with Fabric
In this next installment, John performs the research you might do if your management asked you to examine Fabric.
2024-08-21
3,605 reads
Level 2 of the Stairway to Synapse Analytics: Analyze Data in Storage Account using the Serverless SQL pool
In this second level of the Stairway to Synapse, we learn how to create external tables and query data that is stored in our data storage using the serverless pool.
2025-06-06 (first published: 2024-08-14)
1,039 reads
Microsoft Fabric: Moving Dataflows Gen 2 to different workspaces
Let’s see the steps needed to move a dataflow from one workspace to another. For a matter of example, let’s consider the dataflow access a lakehouse on the Dev environment. When copied to the Test environment, the new copy needs to be linked to a new dataflow in the Test environment.
2024-08-12
2024-08-09
293 reads
Choosing a File Format - Data Engineering with Fabric
In this next article, learn about the different file formats and which work well inside your Microsoft Fabric Lakehouse.
2024-08-07
3,110 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