The Last SQL Server Service Pack
SQL Server 2016 SP3, the last service pack ever is out. Steve comments on how the world of software patches has changed.
Databricks Delta Change Data Feed
In this article we cover how to implement a batch Databricks Change Data Feed process through an end-to-end exercise.
Estimating Data Compression Savings in SQL Server
This video demonstrates a set of queries for estimating data compression savings in SQL Server. It also covers how to make an informed decision on whether data compression makes sense for your data and workload or not.
Choosing State Over Migrations
Steve notes that there are differences between state based development and migration based development, but neither is necessarily better.
Stairway to SSAS Tabular Level 1: Why use Analysis Services
In this first level of the SSAS Tabular stairway, learn the benefits of implementing an SSAS solution.
Learning the SQL GROUP BY Clause
Learn about the various ways to use the GROUP BY command to summarize and rollup query results. We look at the basics with examples as well as using group by rollup, cube and grouping sets.
Tower Loan: Monitoring our estate and insights for your success
Join Kevin Davis, DBA Manager at Tower Loan to hear their playbook for successful distributed estate monitoring, and the role of SQL Monitor.
Incremental Data Loading Using ADF and Change Tracking
This article looks at moving data in three related tables to Azure SQL Database using the change tracking feature in SQL Server to determine which rows have been changed.
Location Data Is Not Anonymous
The world of public data is scary for Steve, even when the data is aggregated. It appears that keeping information private is becoming harder, and perhaps, impossible.
Building blocks of Extended Events data collection
Extended Events have been part of SQL Server since 2008. In this article, Ed Pollack explains the building blocks of Extended Events data collection.
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...
Daily aggregation of Azure Blob Storage by tier (created/tier-change/deleted)
Hello all, I’m looking for advice on how to derive a daily snapshot table...
SQL 2017 to SQL 2025. Good to Go ?
We need to replace our Windows server running SQL 2017. Any reason not to...
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