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Mapping Data Between Systems Print

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Translating between models.

WHY IT IS THE HARD PART

Two systems structure the same information differently.

WHAT DIFFERS

Field names Levels of detail Code sets for the same concept Required and optional fields Validation rules

WHAT A MAPPING IS

A documented correspondence between them.

WHAT TO RECORD FOR EACH FIELD

The source The destination Any transformation What happens when it is absent

WHY THAT LAST COLUMN MATTERS

It is where most integration defects live.

WHAT TO DO ABOUT CODE DIFFERENCES

Maintain a lookup, deliberately, with an owner.

WHAT TO DO ABOUT VALUES WITH NO EQUIVALENT

Decide explicitly: reject, default, or pass through.

WHAT TO NEVER DO

Guess silently.

WHAT TO VALIDATE

That the mapped result is valid in the destination, before sending.

WHY

Rejections at the destination are harder to diagnose than local failures.

WHAT TO PRESERVE

The original message, as received.

WHY

It is the only way to reprocess after fixing a mapping fault.

WHAT TO BE CAREFUL WITH

Dates and time zones Decimal precision Character encoding Names and addresses with unusual characters

WHAT TO TEST WITH

Real data, including the awkward records.


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