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How to combine different versions of same database


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A friend has several versions of the same FileMaker Pro 6 database.

The versions were completed at different times.

Much of the information is the same in each version, but some is unique to one file or another.

The record layouts are not consistent. The same fields can have

different names in different files, and some fields are not found in

every file.

There are over 1000 records per file.

What are some practical, efficient ways to take all the old versions

of the database and use them to create one new combined database,

which will contain all the data from the many existing files?

Thanks for your help.

Brad

FileMaker Version: 6

Platform: Windows 2000

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Welcome Brad!

Sounds like you need to figure out which file has the best structure and use that as your base. Add any needed fields. Then make any cosmetic changes after that.

For the data, I recommend massaging the data in the existing file so it will have a format that will import nicely into the new file. Since each source file is different, you will have to do this differently in each one. You will want to make sure your IDs will work nicely after the import--so take care that these won't overlap (if you have to change your ID numbering, make sure that related records are matched up with the new ID before removing the old IDs.)

Make backups at each stage of the process and clearly label them. It's also a good idea to document the "massaging" steps that you have to go through to get the data ready for import. Go through the steps once offline, then again with the real data after the process is ironed out.

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I'd firstly standardise on field names and change all the databases to conform. Then I'd make a new file (perhaps clone an existing file to save time) with all the fields in it, and import the records from all files.

A cleanup is now performed. Data may need to be entered for those records that had fields missing.

Then begins the process of removing duplicated records. The hard part is working out when records are duplicate: for instance, there may be records for "J Smith" and "J. Smith" little data entry variations like this are going to frustrate you. Often there is no "efficient" method for doing this other than sorting and going through each record manually.

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