The Costs and Rewards of Speaking
Steve has had a good time sharing knowledge with others at events. He gives you a few thoughts on why you might join him at a future event.
How to Build Metadata Driven Pipelines in Microsoft Fabric
Over the past years, “traditional” ETL development has morphed into data engineering, which has a more disciplined software engineering approach. One of the benefits of having a more code-based approach in data pipelines is that it has become easier to build metadata driven pipelines.
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.
Invisible Downtime
Steve has a few thoughts on invisible downtime, a term he had never heard until recently.
Troubleshoot SQL Server Always On Availability Groups with SQL LogScout
We experienced several unplanned outages and failovers on our SQL Server Always On Availability Groups. We want to know the root cause to prevent them from happening in the future. How do we identify the root causes of unplanned Availability Group outages and failovers?
How Big Data Supports Gen AI
This article includes an overview of how big data and Artificial Intelligence (AI) models work together.
Kubernetes is Cool, But ...
Steve has a few thoughts on Kubernetes and how much data professionals should care about the technology.
Recursive CTEs: Transforming and Analyzing Data in PostgreSQL, Part 3
The first two articles in this series demonstrated how PostgreSQL is a capable tool for ELT – taking raw input and transforming it into usable data for querying and analyzing. We used sample data from the Advent of Code 2023 to demonstrate some of the ELT techniques in PostgreSQL.
Realities of Predictive Analysis
Or for short, “Why you have to play the game” “Don't tell me the odds”, cried out Han Solo just before doing something that seemed impossible. How on Coruscant did he do that? Well, as a certain director said about a certain floating door in a galaxy we all call home. ”It was in the […]
Managing SQL Agent in Azure Data Studio
This article continues my series on ADS and examines the SQL Agent extension.
Blogs
SSMS Evaluation – future ready
By Vinay Thakur
In previous posts, we looked at the SQL Server engine. for us DBAs, the...
Claude.ai vs Claude API
By Arun Sirpal
You have used Claude. But which Claude? The Claude app (claude.ai, the desktop and...
T-SQL Tuesday #198–Change Detection
By Steve Jones
This month we have a new host, Meagan Longoria, who graciously agreed to help...
Forums
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Question of the Day
Creating a JSON Document IV
I have this data in a table called dbo.NFLTeams
TeamID TeamName City YearEstablished ------ -------- ---- --------------- 1 Cowboys Dallas 1960 2 Eagles Philadelphia 1933 3 Packers Green Bay 1919 4 Chiefs Kansas City 1960 5 49ers San Francisco 1946 6 Broncos Denver 1960 7 Seahawks Seattle 1976 8 Patriots New England 1960If I run this code, how many rows are returned?
SELECT YearEstablished, json_objectagg(city : TeamName) FROM dbo.NFLTeams GROUP BY YearEstablished;See possible answers