![]() It is possible to forget some columns or rearrange the columns during an import. Even though the calc fields are not shown, the import forces the calcs to run. A table with many calculated fields will slow the import to a crawl.There are a few reasons why we want to, at first, steer clear of the table that holds the data: If I’m adding new students to a student information system, it seems I should directly import them into the Students table.īut that’s not always the case. The first question we should ask: into which table will the data be imported? It seems obvious: the table which holds the data. In a future post, we’ll talk about the best practices of the actual import process: how to script it so any user can perform an import. In this post, we’ll talk about the target table: the table that will receive the data from the FileMaker Data Import. Let’s take a look at best practices for a FileMaker data import. ![]() A few hours later, the import was smooth and quick, and the data was available to all users shortly after the import finished. We took a look at it and talked through it together. The Use Case called for any user to be able to import data from an excel file into the custom app and then work with that data. He was dealing with a slow data import process. I was working with someone from my local user group recently.
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