In reply to Behrouz.

Hi Behrouz,

Thanks for your comment. I'm not personally an expert in SAS Data Quality tools, so I'll ask a colleague to reply too, but your requirement sounds like one which would be well met by one of those tools. If I understand correctly, you are looking for something which can determine whether the each value in a column is a name or not, with a good degree of accuracy, and use the outcome of its row-by-row decision to either set a value in a new column that you can act on in a subsequent step, or to simply blank out the value (or drop the row) if the value is a name. You may be able to write some data step or proc sql code which implements one or two rules of your own to decide if the column contains a name or not, and for simple data, that might work fine. For example, if all the values are either names or phone numbers, and there are no other possibilities, then it is trivially easy to do yourself without any other tools. But if the column can contain values which are strings, and may contain one or two spaces or commas (or whatever other characters your name values can include), then it's harder, because a string may roughly resemble a name without being a name. In that case you would need something which recognises names in strings, based on knowing what likely names exist in your language and country. I think data cleansing step using a SAS Data Quality tool, and a Quality Knowledge Base (QKB) intended for the language and country that the data represents would likely be easier to implement and would work better.

Kind regards,

David