What’s New in SSMS 22
SSMS 22 has several new features. Is there a compilation list of the new features? How will these features help me as a SQL Server professional?
A Full Shutdown
Steve used to shut down systems to upgrade them, but lately he makes changes while they're running.
Going Native with Fabric Spark Pools: The Fabric Modern Data Platform
The next installment of the Fabric Modern Data Platform looks at Spark pools for executing code.
Getting Started with mssql-python for Data Developers
rogrammatic interaction with SQL Server or Azure SQL from a Python script is possible using a driver. A popular driver has been pyodbc that can be used standalone or with a SQLAlchemy wrapper. SQLAlchemy on its own is the Python SQL toolkit and Object Relational Mapper for developers. In the end of 2025 Microsoft released v1 of their own Python SQL driver called mssql-python. How do you get started using mssql-python for programmatic access to your SQL Server?
Designing Delta Tables with Liquid Clustering: Real-World Patterns for Data Engineers
Get a short introduction to Liquid Clustering in Databricks.
Fun with JSON
Last year, I used a lot of JSON to exchange data between systems. There are several ways to extract data from a JSON file, but there is one specific, probably less-used possibility that I’d like to highlight. For one project, I received JSON files containing a variable number of parameters and their values. If I […]
Not Just an Upgrade
Choosing to upgrade isn't as simple as many of us would like. Steve has a few thoughts today on the decision to move to a new version of a database server.
SQL Server Long-Running Query Detection: How to Find and Monitor Slow Queries
Monitoring and alerting can be overwhelming tasks, especially for those new to the world of managing production data. One common challenge for any data professional is the identification and management of queries that run for longer than they should.
Metadata Driven Pipelines (Incremental Load): The Fabric Modern Data Platform
This article will use the incremental data load pattern to load data in our raw zone tables.
Why End-User Testing Is Even More Important with AI
I don’t think I’m alone in this frustration, but it crystallized for me recently while trying to do something that should have taken less than two minutes: check in for a flight. What followed was a cascade of app switching and authentication failures. I started in my favorite travel app, moved to one airline app, […]
Blogs
T-SQL Tuesday #198 Invitation: How Do You Detect Data Changes?
It's time for T-SQL Tuesday #198! This month's topic is change detection. The post T-SQL...
Understanding Fabric MCP
By James Serra
Model Context Protocol, or MCP, is one of those technical ideas that sounds more...
AWS RDS Aurora - our first approach
When starting with AWS RDS Aurora for managing relational databases in the cloud, many...
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Question of the Day
Creating a JSON Document III
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 TOP 2
json_objectagg('Team' : TeamName)
FROM dbo.NFLTeams;
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