Replace Bad Characters in Table
Learn how to clean bad characters from lots of data in this article.
Generating HTML from SQL Server Queries
You can produce HTML from SQL because SQL Server has built-in support for outputting XML, and HTML is best understood as a slightly odd dialect of XML that imparts meaning to predefined tags. There are plenty of edge cases where an HTML structure is the most obvious way of communicating tables, lists and directories. Where data is hierarchical, it can make even more sense. William Brewer gives a simple introduction to a few HTML-output techniques.
Classifying Sensitive Data
The ability to protect, and perhaps handle, sensitive data separately from other data is becoming more important. Steve Jones discusses the process and asks if it's something you perform on a regular basis.
Filegroup Restoring and Database Consistency
In this article, we'll explore a less used feature of SQL Server: filegroup restoring, feature that has an interesting consequence because database can become inconsistent without any warning and standard checks don't reveal any issue.
How to Read the Transaction Log File
Have you ever wanted to be able to see the actual transactions that are contained in the transaction log file? Greg Larsen shows you how to browse the transaction log using an undocumented function.
Improving Replication
If you have ideas for how to improve replication, Steve Jones is asking for them.
The Forgotten Editorial
Phil Factor reflects on the occasional benefits of document loss, whether accidental or less so.
Workplace Encounters: Using Volume Mount Points in SQL FCIs
How we overcame the A to Z Windows Drive-Letter limitation using Volume Mount Points
A DLM Approach to Database Testing
Database Lifecycle Management aims to make the development and modification of databases more predictable. Bugs are the source of more unpredictability than anything else, purely because it is so difficult to guess how long it will take to fix them. Good testing at all stages may take some time and effort, but it greatly reduces likelihood of the wildcard factor of the bug that is first detected during the deployment process; or worse, that gets into the production release.
Blogs
Overcoming Challenges: Navigating Common Pitfalls in FinOps Adoption
By HeyMo0sh
Working in DevOps, I’ve seen FinOps do amazing things for cloud cost control, but...
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...
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