We had a situation recently where test records, created by processes upstream of our data warehouse, were causing issues with our data. Since the test records were created by many different groups, their names didn't follow any pattern, so they were not easy to exclude. We ended up having where clauses like this in many different stored procedures:
Where
StoreName not like '% test st%'
and StoreName not like '% test 2%'
Keeping these updated across all the stored procedures was a hassle, so test records were continually getting into our data and causing problems.
I decided to create one metadata table for all the test patterns, and then create a view to join to that table. The view would be used to exclude all the test records whenever necessary.
First, let's create the sample data:
Create Table TestStoreNameWildcard(WildcardPattern varchar(50))
Insert into TestStoreNameWildcard
values
('% test st%')
,('% test 2%')
,('% test 3%')
,('%test region%')
Create table Store (StoreID int, StoreName varchar(50))
Insert into Store values
(1, 'Corner Store')
,(2, 'ABC Store')
,(3, 'Region A Test Store')
,(4, 'Test Region 1 Store')
,(5, 'Region 5 Test 2 Store')
,(6, 'Target')
,(7, 'Contest store')
,(8, 'Ann''s Book Store')
Now create a view that returns only those stores which fit our pattern, joining with "like".
Create view vTestStore as
Select
StoreID
,StoreName
from Store
join TestStoreNameWildcard
on Store.StoreName like TestStoreNameWildcard.WildcardPattern
Now, when you run this select:
Select * from vTestStore
You'll see only those stores that we've identified as test stores. The view vTestStore can be used to exclude test records wherever needed. If performance is a problem, it could be created as a table or indexed view.
StoreID StoreName
----------- --------------------------------------------------
3 Region A Test Store
5 Region 5 Test 2 Store
4 Test Region 1 Store