I tried to google this but I didn't know how to write it without needing to explain myself.
Basically I have a data set that I am performing some validation on, and I am looking for duplicate data imports from users of the database I am working on.
The reason for this is that the users have been importing building information into the database. In some cases, the name (for example) has been incorrect, and so they have amended the import file and re uploaded the data.
The issue is that rather than replacing the existing building, the importer (understandably) creates new building records. So I need a way to return building records that have a duplicate, so that we can remove the older records.
Obviously this is not perfect, but I'm trying to use common fields (building size, location) to locate duplicates, as these fields would be the same; it's only the names that would have changed. So I if I were to have tables laid out as below, how would I isolate the duplicate rows? (sorry for the imgur link, I don't know how to format text here into a table-like format; the table is very much simplified)
https://i.stack.imgur.com/p9D98.jpg
So you can see that the buildings at LocationID 1 and 4 have only been imported once, but the import for LocationId 2 has been run twice and 3 times for LocationID 3 - these are the records I need to find.
I simply want to know if there is something I can use to isolate rows where a series of columns are duplicated - can anyone help?