Outlier Detection with SQL Server, part 3.1: Grubbs’ Test
By Steve Bolton
…………In the last two installments of this series of amateur self-tutorials, I mentioned that the various means of...
2014-12-03 (first published: 2014-11-29)
11,089 reads
Outlier Detection with SQL Server, part 2.2: Modified Z-Scores
By Steve Bolton
…………There are apparently many subtle variations on Z-Scores, a ubiquitous measure that is practically a cornerstone in the...
2014-11-13
2,469 reads
Outlier Detection with SQL Server, part 2.1: Z-Scores
By Steve Bolton
…………Using SQL Server to ferret out those aberrant data points we call outliers may call for some complex...
2014-10-28
2,834 reads
Outlier Detection with SQL Server, part 1: Finding Fraud and Folly with Benford’s Law
By Steve Bolton
…………My last blog series, A Rickety Stairway to SQL Server Data Mining, often epitomized a quip by University...
2014-09-19
3,344 reads
Stay Tuned…for a SQL Server Tutorial Series Juggling Act
by Steve Bolton
…………If all goes according to plan, my blog will return in a few weeks with two brand new...
2014-07-01
700 reads
A Rickety Stairway to SQL Server Data Mining, Part 15, The Grand Finale: Custom Data Mining Viewers
By Steve Bolton
…………As mentioned previously in this amateur self-tutorial series on the most neglected component of Microsoft’s leading database server...
2014-02-17 (first published: 2014-02-11)
2,060 reads
A Rickety Stairway to SQL Server Data Mining, Part 14.8: PMML Hell
By Steve Bolton
…………In A Rickety Stairway to SQL Server Data Mining, Part 14.3: Debugging and Deployment, we passed the apex...
2014-01-15
1,598 reads
A Rickety Stairway to SQL Server Data Mining, Part 14.7: Additional Plugin Functionality
By Steve Bolton
…………In order to divide this segment of my amateur tutorial series on SQL Server Data Mining (SSDM) into...
2014-01-07 (first published: 2013-12-31)
2,257 reads
A Rickety Stairway to SQL Server Data Mining, Part 14.6: Custom Mining Functions
by Steve Bolton
…………In the last installment of this amateur series of mistutorials on SQL Server Data Mining (SSDM), I explained how to...
2013-12-06 (first published: 2013-11-28)
2,678 reads
A Rickety Stairway to SQL Server Data Mining, Part 14.5: The Predict Method
By Steve Bolton
…………In order to divide the Herculean task of describing custom algorithms into bite-sized chunks, I omitted discussion of...
2013-11-04 (first published: 2013-10-30)
2,776 reads
Blogs
AI: Blog a Day – Day 4: Transformers – Encoder, Decoder, and Attention
By Vinay Thakur
Continuing from Day 3 where we covered LLM models open/closed and their parameters, Today...
Flyway Tips: Multiple Projects
By Steve Jones
One of the nice things about Flyway Desktop is that it helps you manage...
What DevOps Look Like in Microsoft Fabric
By HeyMo0sh
Microsoft Fabric (not to be confused with the more general term “fabric” in DevOps)...
Forums
Can an Azure App Service Managed Identity be used for SQL Login?
I'm fairly certain I know the answer to this from digging into it yesterday,...
Azure Synapse database refresh
Hi Team, I am trying to refresh the Azure Synapse Dedicated pool from production...
how to write this query?
hi everyone I am not sure how to write the query that will produce...
Question of the Day
Fun with JSON I
I have some data in a table:
CREATE TABLE #test_data
(
id INT PRIMARY KEY,
name VARCHAR(100),
birth_date DATE
);
-- Step 2: Insert rows
INSERT INTO #test_data
VALUES
(1, 'Olivia', '2025-01-05'),
(2, 'Emma', '2025-03-02'),
(3, 'Liam', '2025-11-15'),
(4, 'Noah', '2025-12-22');
If I run this query, how many rows are returned?
SELECT *
FROM OPENJSON(
(
SELECT t.* FROM #test_data AS t FOR JSON PATH
)
) t; See possible answers