Thank you Kevin
Sage advice.
Cheers
Jeremy.

"Kevin Zawicki" <numberjack@wi.rr.com> wrote:
>
>But then why not clean up table 1 and change custname to in table 2 to match
>table 1 based on Cust Code to start?
>Then you know all custcodes have same name in both tables.
>Then if you might have a cust name in both with different cust code, find
>all cust codes in each table that are not in the other?
>
>Or maybe
>1       00301       MOOROOLBARK SECONDARY COLLEGE
>2       00301       MOOROOLBARK COLLEGE
>
>I would have tcursors scan the CustName column and break cust name into
words
>on spaces, and put in another table, doing this on both tables into one
table
>
>Seqnum | tablenum | custcode | word |
>---------------------------------------
>1        1          00301      MOOROOLBARK    
>2        1          00301      SECONDARY  
>3        1          00301      COLLEGE
>4        2          00301      MOOROOLBARK   
>5        2          00301      COLLEGE  
>
>Then do some sum counts on common words by cust codes.
>
>My experience is that you cannot full automate this, you have to use the
>code and analyze to find, then edit / cleanup
>
>
>
>
>
>"Jeremy Stagg" <jeremy.stagg@itsysadmin.com.au> wrote:
>>
>>Hi Kevin
>>
>>Both databases have the same Customer table structure and keyed:
>>
>># | Field Name | Type | Size | Key
>>----------------------------------
>>1   Cust Code    A      5      *
>>2   Cust Name    A      35    
>>
>>There are discrepancies between the two tables / databases by Cust Code
>and
>>then Cust Name.
>>
>>Examples are:
>>
>>Table | Cust Code | Cust Name
>>-----------------------------------------
>>1       00301       MOOROOLBARK SECONDARY COLLEGE
>>2       00301       MOOROOLBARK COLLEGE
>>1       08415       BACCHUS MARSH COLLEGE
>>2       08415       BACCHUS MARSH SECONDARY COLLEGE
>>1       07179       BAKER MEDICAL RESEARCH INSTITUTE
>>2       07179       BAKER IDI HEART & DIABETES INSTITUTE HOLDINGS
>>
>>There are % similarities to identify and grade, allowing for a quick remediation
>>and then can consolidate the data sets.
>>
>>The Cust Code is the pinacle key as there are more structures stemming
from
>>this, such as Customer Address.
>>
>>I'm making Table 1 the Gold Master and making changes only in Table 2.
>>
>>Hence the fuzzy logic.
>>
>>Have used the Google Sheets solution from:
>>https://stackoverflow.com/questions/70989502/fuzzy-matching-in-google-sheets
>>
>>And looking at this it still says to me Paradox could do it.
>>
>>
>>"Kevin Zawicki" <numberjack@wi.rr.com> wrote:
>>>
>>>Can you be more specific?
>>>Are they keyed?
>>>Two tables with same customer key # or name or anything?
>>>If the two tables have any data field the same and you are looking for
>record
>>>level differences you could join the two tables and check all and use
!,
>>>something like that.
>>>Need more info…
>>>
>>>
>>>
>>>
>>>"Jeremy Stagg" <jeremy.stagg@itsysadmin.com.au> wrote:
>>>>
>>>>Hi to All
>>>>Wondering if anyone has scripted in ObjectPAL fuzzy logic for identifying
>>>>text matches in columns between two tables?
>>>>I have to identify matches between two separate tables of customers (separate
>>>>databases) that have "drifted" and looking to merge the two.
>>>>Cheers
>>>>Jeremy.
>>>
>>
>