Coping with a working life as an imposter
It is not existing knowledge but the skill of acquiring new knowledge rapidly that will help you overcome imposter syndrome.
Fixing Impostor Syndrome
Lessons on impostor syndrome from a marketer apply to technologists as well.
The Degradation of the Turing Test
Are computers getting smart enough to pass the Turing test or are humans getting worse at representing themselves as intelligent?
What Can AI Really Do?
Steve asks you what you think AI can do for you today, with a few suggestions of what he sees.
Why Your Index Isn't Being Used? - Reading Execution Plans to Find the Real Culprit
Built the index, but SQL Server still scans the whole table? Learn how to read execution plans and find exactly why your index is being ignored.
Improve Query Performance in the Fabric Warehouse with Clustering
Learn how to improve performance issues in Microsoft Fabric Warehouse and leverage cloud-based data analytics effectively.
We Are Eating Our Own Seed Corn
Last week I stood in front of a classroom at Washington State University and looked out at a room full of students who had done everything right. They had studied hard, were earning their degrees, built their portfolios, and showed up with genuine enthusiasm for careers in technology. They wanted to know what the industry […]
Designing SQL Server ETL Pipelines That Don't Break at Scale
A few lessons learned in building ETL pipelines and tricks to ensure you can easily maintain these over time.
Why I Don’t Like Shared Development Databases
Today, Kendra explains why she doesn't like shared development databases.
When, and when not, to use LLMs in your data pipeline
LLMs should be used in data pipelines for unstructured text, semantic search, and natural language queries – but avoided for deterministic, high-volume, or regulated tasks. Drawing on my real-world experience building large-scale ML systems, in this guide I’ll explain exactly where LLMs belong in your data pipeline and, just as importantly, where they don’t.
Blogs
Understanding Fabric Ontology
By James Serra
What problem is Fabric Ontology trying to solve? For years, most data conversations have...
QUOTENAME Basics: #SQLNewBlogger
By Steve Jones
Recently I ran across some code that used a lot of QUOTENAME() calls. A...
When growing companies outgrow Excel
By ChrisJenkins
There are some telltale signs that your growing business has outgrown Excel for your...
Forums
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Question of the Day
QUOTENAME Quote Parameters
When I use QUOTENAME(), I can optionally provide the character used to surround the string in the result. Can I use any character?
See possible answers