Data: Lost in Translation
Whether you are setting up an ongoing integration or preparing for a one-time migration, there will be situations where a ‘single-select’ or a similar field type’s data in one system is not what the other system accepts. The list values may be very similar but not the same in both systems. Contextually as a user, you know what values equate each other, but if they aren’t identical, then how do you consistently automate this in your integration or migration?
The Structure
To start, you will need a table of data containing at least two columns. Each column represents one of your systems and contains all the selectable options for the ‘connected’ fields from each system. Each row in the table is where you connect the related list value options between the columns. Connecting the related values in the rows is the most important part of the table since this is how you define which values translate to each other.
The Principle



The Takeaway
Knowing how to translate your data between systems is exactly like what translators do to communicate a message from one language into another. So, mastering the structure and principle behind translating your data is how you or your integration becomes the translator and ensures that your data never gets lost in translation.
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