Topic: Grouping on inferred data Posted: 16 Apr 2010 at 10:43am
I need to group on data that doesn't exist. This client has customer records that have understood metagroupings that aren't in the database. So the customer list might look like:
Bill's Stuff Ted's things Sam's Industries Sam's Organization Fred's store Ted's Main Office George's shop
When they summarize the records, they want to group all of Sam's and Ted's sales records together, and leave the other clients grouped as they are.
My constraints: Can't alter the database schema, it is a purchased system and the UI is tightly coupled to the schema I can add a numeric code for the metacustomers in an unused "accountcode" field The records are actually named so that I can do string trickery "If the first six letters are the same group together" but I don't know how to do that"
The question - what is best practice for this kind of grouping, where you have to interpolate the grouping data?
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Posted: 16 Apr 2010 at 12:43pm
I don't know that there is a best practice as each data set and each customers use of that dataset (business rules) are unique.
Since you know unique condition (left 6 characters) you can easily group by creating a formula field and grouping on that. However I would guess you would rather create a group of just the person's name which allways precedes the '. So I would try the formula as;
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