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In processing and formatting your data, you may decide that some records should be classified as Null values. Rather than fill in numeric fields with a 0 or leave a field empty (‘’), a Null value may be the best option for analyzing and storing your data.
In this particular example, let’s pretend that we have customer IDs and the phone numbers associated with them. Some phone numbers may be incomplete or mistyped.
After removing punctuation with the Data Cleansing Tool, we’ll look for valid phone numbers – those composed of 10 digits – to store in our Customer database.
To identify our valid results, we’ll apply a conditional statement: IF a phone number is not 10 digits long, THEN the record is Null; otherwise (ELSE) use the phone number in our data.