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About Bmiller4evr

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  1. So, TrimAll ( Situs_St_Prefix&" "&Situs_St&" "&Situs_Sufix&" "&Situs_St_Dir ; 0 ; 0 ) will do this for me?
  2. I have a series of fields pertaining to physical addresses: they are Street Prefix, Street Name, Street Suffix, Post Directional Situs_St_Prefix - ex: North, South, NW, ect or blank Situs_St - Main, Elm, FM 157, County Road 6, Keller Elliott, SW 5th Situs_Sufix - Road, Street, DR, Circle Situs_Dir - N, S, E, W These need to be combined into a full address, but I can not simply use &" "& because often some of these fields are blank and that generates extra blank spaces next to non-existant fields. My next thought was to use a series of If statements, to crea
  3. Any way to index the cFlag? running a query on cFlag for 1.5million unstored seems to be taking some time.
  4. the customer name list is 1.5million, the black list is about 100 names, if I had to guess I would say that about .5% of the customer names need to be blacklisted. The process needs to run as often as the database is updated, which is typically bimonthly.
  5. I do not think I can use a name match to achieve my objective. To add a further point of clarification. The names on the 'black list' are typically only a portion of customer name field, not an entire match. An example - *are customer names that need to be blacklisted Customer Names: Smith, James Jones, Edward and Stacy Hertz, Sam Living Trust* Hartford LTD* JPMorgan Chase Bank* Blacklist: Bank LTD Trust the blacklist serves as a means to identify a specific type of property owner.
  6. Any way to check for the presence of a given word in any location within a field?
  7. I have a group of records, one of the fields is a a Customer Name (not unique). On another table I have a list of names that have been added to a blacklist. I need a calculation field that will compare the customer name to the black list to see if they have been flagged.
  8. Here is your table back Comment. It more accurately reflects how my data is stored. http://dl.dropbox.com/u/24727871/Ownerships.fp7
  9. If in your example George is the most recent prior owner, how does that calculation get made so that it compares George's deed date with the Current owner in primary table?
  10. Vaughan, that does certainly help. I guess the next step would be to add a field in the Prior owner table so that each record would calculate the time between the date on that record and the deed date of the current owner on the primary table. Someone please tell me what function would do that.... but how would this new field know to relate to the primary table or other records in the prior owners table if it was a record of say 2 or 3 owners ago?
  11. No, it is not the best starting point. I did not choose for the records to be kept that way. What is the calculation that will measure the time between the 2 dates? how will it know which 2 dates to calculate between if there are multiple prior owners? When I display in a portal I can sort, but if I create a new field that shows time of ownership (hopefully u can provide the calculation) how will it know which of the prior deed dates to compare with?
  12. About the data. I have 1 table that contains current ownership information about real property and the date it was purchased. Each piece of real property has a unique account number. In a second table I have prior ownership information about the real property, if prior ownership records are in existence, then the account number exists and the date the owner bouts the property is recorded with the owners name, address, ect. Some property records have no prior owners, and some have several, in those instances the unique account number from the first table will be present in the second table
  13. Thank you again. Using GetField ( "Zipcodes::" & Column ) works great. Unfortunately I am doing the same thing with a different set of county records now and they do not store their mapsco coordinates in the same way. Perhaps you could give some assistance on calculating from a field in a different way. Here is a sample of the data: 66-a (dallas) 55-z (dallas) 9-r (dallas) 29a-v (dallas) 19a-f (dallas) 30a-x (dallas) 36-e (dallas) 4b-k (dallas) on this particular mapsco they had to go back and add in additional pages to include areas further out that was orig
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