One approach might be to import whatever you can get into a temporary table
in Access, then run queries that "coerce" the data into a final data
type/format in more permanent tables. I use "tables" because Excel data is
usually "flat", where a well-normalized Access application uses relational
data (table) structures.
Regards
Jeff Boyce
Microsoft Office/Access MVP
> Hello,
>
[quoted text clipped - 28 lines]
> treated
> like numbers?
mklapp - 29 Sep 2006 21:34 GMT
Actually, that was pretty close. I change the column to Text and loaded the
rows. Used a Find and replace to remove quotation marks ( one at a time.
The command would not get both in the same 'cell'. Had to redefine the data
type a couple of times because Access kept truncating the cents.
I conditioned the Excel data into a nicely normalized table on each sheet
and followed what anyone would have called due diligence in preparing the
sheets for import. The frustrating thing was the indeterminate behavior of
Access. There was absolutely no condition that was useful in predicting or
controlling the behavior. That may be acceptable for some types of fantasy
AI but NOT for a database or spreadsheet application.
> One approach might be to import whatever you can get into a temporary table
> in Access, then run queries that "coerce" the data into a final data
[quoted text clipped - 39 lines]
> > treated
> > like numbers?
Jeff Boyce - 30 Sep 2006 00:30 GMT
Actually, I was recommending doing the work inside of Access, importing all
the "raw" Excel data first.
Regards
Jeff Boyce
Microsoft Office/Access MVP
> Actually, that was pretty close. I change the column to Text and loaded
> the
[quoted text clipped - 65 lines]
>> > treated
>> > like numbers?
mklapp - 29 Sep 2006 21:35 GMT
BTW - Thanks for your response.
> One approach might be to import whatever you can get into a temporary table
> in Access, then run queries that "coerce" the data into a final data
[quoted text clipped - 39 lines]
> > treated
> > like numbers?