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Large Match/Identify Situation - Looking for suggestions

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  • Large Match/Identify Situation - Looking for suggestions

    Greetings fellow developers !

    I have a task to accomplish and I thought I would bounce it off this list and see if someone had a better approach to the situation. I have
    V11 available to work with.

    I am working on a specialized auditing project and one of the tasks is to identify "government" customers that this client sells to. Normally,
    this is not too tough as the customer file may be coded (flagged) with a customer type field denoting "government" accounts and our task
    is to browse thru the list of those accounts to verify that they are in fact "government" accounts and look for others in the remaining potion
    of the customer file that have not been so noted. Usually this is anywhere from a few hundred to ten thousand and can easily be done in
    a tool such as Excel. But not this project !!

    The Customer File is in excess of 1 Million customers and over 1 gig of data for that file. Also there is not a customer type field with a value
    for government account, either.

    So the approach I am considered is the following....

    -I have loaded the entire Customer File into A5.
    -I have built another table containing typical government entity naming (words) such as:
    City, County, Parish, University, AAFES, Army, Navy... etc.

    Now I was thinking about bouncing the "term list" against the names in the Customer Table and "Marking" those records.

    I will still have to scroll thru and determine whether the "marked" records and in fact potential accounts... an example of what
    I will have to deal with is: City of Chicago... Chicago, City of... Fun City... the later is most likely NOT a government
    account even though it contains the word "city" in it.

    Browsing thru the "marked" records and "un-marking" items that are not in all likelihood government accounts, should leave
    me with a "marked" list that I could either export OR add a coding field too for future reference.

    Since the "term list" is about 40 items and the customer file is in excess of 1 million, I expect that this process will take a while to
    run in the first place... and hopefully not select an excessive amount of possible matches (fingers crossed here).

    Anyone have what they think might be a better approach that they would be willing to share?

    Regards,
    Keith
    Keith Weatherhead
    Discus Data, Ltd
    kweatherhead@gmail.com

  • #2
    Re: Large Match/Identify Situation - Looking for suggestions

    Is there any pattern to the fields in the records? Is your search criteria limited to a few fields or do you have to search all of them?

    You have probably thought of this, but it has to be mentioned.

    Is there a chance any or hopefully all the records have email addresses? If so a search for .gov, .org and whatever else might be used for marking a government agency record. If this eliminates only 10 percent of the records from your search it would be a huge help.

    If your search finds “City of” and it always indicates a government agency, you might want to run a search on that criteria first, mark and export those records. There may be other cases, such as the email one mentioned above, where this might help eliminate some of the hits and/or misses before you do a table based search. This might take more CPU time, but if it eliminates human time it’s a winner. Using the concept of, “Search within results whenever possible”, when doing a sort is generally a good rule.

    These are probably not the best suggestions, but your response to what might seem dumb might help others better understand what you are dealing with.

    All the Best,
    Rich

    Comment


    • #3
      Re: Large Match/Identify Situation - Looking for suggestions

      Rich,

      Thanx for your comments. Unfortunately there is NOT an email field in the data. I really only need to search one field, the Customer Name field. While there are many other fields including the address and phone number fields, they are really of no more help in reality.

      My thoughts were to simply take the "terms" I have identified over-the-years as governmental agency keys and search for them in the Customer Name only and mark the
      records if there is some sort of match. I am not sure if I want to extract (export) after every pass as I would end up with about 40 pieces to reassemble, after passing through my "terms" list. Once the "terms" list has been applied and all potential records marked, then run thru that list one time to get to my candidates list. I am hoping, going forward that this client will add a flag field for this purpose cause they are going to have to track this information in the future and it would help to make this process a bit more palatable, however, you have to start somewhere when the information does not initially exist.

      Regards,
      Keith
      Keith Weatherhead
      Discus Data, Ltd
      kweatherhead@gmail.com

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