Joe Celko explores the dangers of muddling correlation and causation, emphasises the importance of determining how likely it is that a correlation has occurred by chance, and gets stuck into calculating correlation coefficients in SQL. Along the way, Joe illustrates the consequences of leaping to the wrong conclusion from correlations with tales of Pop Dread.
2009-10-19
2,136 reads
2009-10-16
5,101 reads
2009-10-14
4,697 reads
Often in database design we store different values in rows to take advantage of a normalized design. However many times we need to combine multiple rows of data into one row for a report of some sort. New author Carl P. Anderson brings us some interesting T-SQL code to accomplish this.
2011-03-04 (first published: 2009-10-14)
150,384 reads
How the JOIN operator works, the different types of JOINs and relevant information about joining tables.
2011-03-03 (first published: 2009-10-07)
47,586 reads
Retrieve consecutive records from the table based the value difference
2009-11-04 (first published: 2009-10-06)
946 reads
2009-10-02
4,633 reads
2009-10-21 (first published: 2009-10-01)
2,298 reads
In development enviornment we always get the modifications in tables from developers.As far as my concern writing scripts is tedious work for us. I hope below script will help you.
2009-10-30 (first published: 2009-10-01)
1,347 reads
2009-10-01
4,179 reads
In last months one of the scenarios where you can use AI has been...
By ChrisJenkins
Do you spend so long manipulating your data into something vaguely useful that you...
By Steve Jones
It was neat to stumble on this in the book, a piece by me,...
Comments posted to this topic are about the item Creating JSON II
Comments posted to this topic are about the item Engineer Lessons
On SQL Server 2025, what happens when I run this code:
SELECT JSON_OBJECTAGG( N'City':N'Denver' RETURNING JSON) GOSee possible answers