During an initial exploration of a CRM export that will feed a data warehouse, you notice the staging table contains two seemingly identical columns-Customer_ID and CRM_Customer_GUID. To test whether one column is a redundant copy of the other, you execute:
SELECT COUNT()
FROM staging.crm_sales
WHERE Customer_ID IS DISTINCT FROM CRM_Customer_GUID;
The query returns 0 rows. Based solely on this result, which conclusion is most appropriate?
The two columns store the same values in every record, so keeping both is redundant and one can be dropped.
Because there are no mismatches, Customer_ID must be a foreign key that references CRM_Customer_GUID, so both columns should remain.
The test shows that each column is unique but represents a different business key, so no redundancy exists.
Zero mismatches prove the table contains duplicate rows, so both columns are needed to remove those duplicates later.
The predicate IS DISTINCT FROM returns TRUE only when the two compared expressions differ, treating NULL as a normal value. Because the query returned no rows, it means there is no record in which Customer_ID and CRM_Customer_GUID differ (including no mismatched NULLs). Therefore the two columns carry identical information for every row, so retaining both adds unnecessary storage and maintenance overhead-one of them can be removed. The other options misinterpret the result: a lack of mismatches does not imply duplicate rows, identify different business keys, or reveal a foreign-key relationship. It simply shows the columns are equivalent and hence redundant.
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