Slowly Changing Facts
This article describes a design pattern for storing “effective dated" changes to fact tables.
2013-10-18 (first published: 2010-12-22)
20,820 reads
This article describes a design pattern for storing “effective dated" changes to fact tables.
2013-10-18 (first published: 2010-12-22)
20,820 reads
Describes a design pattern for using CDC to power fast and efficient incremental data loads.
2013-06-07 (first published: 2011-01-17)
29,248 reads
This article describes a technique of using FULL JOINs to compare two datasets within a numerical tolerance.
2013-04-23 (first published: 2010-09-27)
30,880 reads
By James Serra
Making Data AI-Ready, Part 3 (This is the final article in a three-part series...
By Steve Jones
I use ConEmu for my terminal interface. I’m still on Windows 10 at home,...
Creating a Fabric workspace takes about 30 seconds. Restructuring workspaces after people have built...
Comments posted to this topic are about the item Adding new column with DEFAULT...
Comments posted to this topic are about the item Advanced Deployment Scenarios: Stairway to...
Comments posted to this topic are about the item You Need a DBA Pipeline
Which number did the two COUNT(*) return:
DROP TABLE IF EXISTS #tmp CREATE TABLE #tmp (id INT NOT NULL) INSERT INTO #tmp (id) SELECT gs.value FROM GENERATE_SERIES(1, 5) AS gs ALTER TABLE #tmp ADD my_value INT NOT NULL CONSTRAINT df_tmp_my_value DEFAULT 1 SELECT COUNT(*) FROM #tmp AS t WHERE my_value = 1 ALTER TABLE #tmp DROP CONSTRAINT df_tmp_my_value ALTER TABLE #tmp ADD CONSTRAINT df_tmp_my_value DEFAULT 2 FOR my_value SELECT COUNT(*) FROM #tmp AS t WHERE my_value = 1See possible answers