Advice I Like: Knots
Learn how to tie a bowline knot. Practice in the dark. With one hand. For the rest of your life, you’ll use this knot more times than you would...
2026-03-13
14 reads
Blog Posts
AI: Blog a Day – Day 3: LLM Models – Open Source vs Closed Source
Continuing from Day 2 , we learned introduction on Generative AI and Agentic AI, Today on Day 3 I would like to write about LLM models — Open Source...
2026-03-13 (first published: 2026-03-03)
338 reads
Rolling Back a Broken Release
We had an interesting discussion about deployments in databases and how you go forward or back from the point when you discover a problem. You can watch the episode...
2026-03-13 (first published: 2026-02-23)
268 reads
Shifting Mindsets: Why FinOps is Essential for Cloud Efficiency
As a DevOps practitioner, I’ve always focused on performance, scalability, and automation. But as cloud adoption has matured, I’ve come to realise that building and running great systems isn’t...
2026-03-12
13 reads
Deployment Pipelines in Fabric – What Are They?
In the realm of software development and content creation, the deployment pipeline serves as a crucial bridge between innovation and implementation. Whether you are fine-tuning code, testing new features,...
2026-03-11 (first published: 2026-03-03)
275 reads
How to Parameterize Fabric Linked Services in Azure Data Factory for Azure Devops Deployment
Quite the title, so let me set the stage first. You have an Azure Data Factory instance (or Azure Synapse Pipelines) and you have a couple of linked services...
2026-03-11 (first published: 2026-03-03)
326 reads
T-SQL Tuesday #192: What career risks have you taken?
This T-SQL Tuesday is hosted by the one and only James Serra – literally my go-to guy for data lakes and BI architecture. I am so tickled to be...
2026-03-10
13 reads
T-SQL Tuesday #196: Taking Risks
This month we have a new host, James Serra. I’ve been trying to find new hosts over the last few years to keep this party going and to expand...
2026-03-10
11 reads
AI: Blog a Day – Day 8: RAG – Retrieval Augmented Generation
RAG — Retrieval Augmented Generation. we have covered so far — embeddings, vectors, vector databases — all comes together here! What is RAG? all the AI model has predefined...
2026-03-09 (first published: 2026-03-08)
20 reads
AI: Blog a Day – Day 9: HuggingFace – The Home of AI Models
today on Day 9 I would like to talk about HuggingFace. if you are learning AI practically, HuggingFace is one of the most important platforms you will come across....
2026-03-09
Blogs
Who Are You Doing It For?
By Brian Kelley
But as I've matured over the years, I came to realize that I needed...
Presenting Twice in May 2026
By alevyinroc
I will be presenting my latest session, Documenting Your Work for Worry-Free Vacations, in-person...
Finding the Next Sequence Value: #SQLNewBlogger
By Steve Jones
I saw a question asking about the next sequence value and decided to try...
Forums
DB Design Methods
I've read a few posts regarding what we use to design DB models and...
Auto Update Statistics not triggering on filtered indexes
I've got a table with 186,703,969 rows, about 300GB of data. There are several...
What is the difference between SQL Server and SQL Database?
I created a SQL Database in Azure Portal but I've just noticed it also...
Question of the Day
An Unusual Identity
What values are returned when I run this code?
CREATE TABLE dbo.IdentityTest2
(
id NUMERIC(10,0) IDENTITY(10,10) PRIMARY KEY,
somevalue VARCHAR(20)
)
GO
INSERT dbo.IdentityTest2
(
somevalue
)
VALUES
( 'Steve')
, ('Bill')
GO
SELECT top 10
id
FROM dbo.IdentityTest2 See possible answers