Re: Identifying Numeric Columns with Bad Data - S36 DDS Conversion

It depends on how you want to handle the "bad" fields.

If you want to know -which_ fields have the problem (usually a good idea so that you can identify the source and fix it) then a simple approach is to use a DS laid out as the record should be, do a READ into the DS (which prevents the "bad" fields from throwing an error) and then just perform a simple operation stepping through each numeric field using MONITOR to trap for bad numerics and fixing/reprting them as required.


Jon Paris
Jon.Paris@xxxxxxxxxxxxxx

On Mar 16, 2026, at 10:29 AM, Richard Schoen <richard@xxxxxxxxxxxxxxxxx> wrote:

Hi All,

Doing a S36 conversion to add DDS/DDL to tables.

Is there a good methodology to check for decimal data errors on columns and fix them quickly ?

We do a CPYF *NOCHK to populate the tables.

And I’ve seen SQL function “systools.validate_data” as one possible method.

Thoughts appreciated.

Regards,
Richard Schoen
Web: http://www.richardschoen.net
Email: richard@xxxxxxxxxxxxxxxxx

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