Transformation rule
A transformation rule defines how input data becomes destination values. The calculation, prerequisites and error cases need describing together.
A transformation rule describes how data is reshaped or calculated when moving from source to destination. It can map fields, change data types or derive a destination value from inputs, for example. The business meaning of the inputs determines which rule fits.
Describe a quantity conversion precisely
In a fictional exchange, 2 cartons containing 6 items each correspond to a destination quantity of 12 items. The rule may apply only when the packaging unit and pack factor are known for this item. If the factor is missing, the case needs clarification; an unchecked substitute value would invent a quantity.
Check calculation and validity separately
Microsoft shows derived columns that generate new values or modify existing fields. Such functions implement agreed logic. They do not decide for themselves whether the conversion is valid for the business. Record the prerequisites, expected result and behaviour when information is missing before checking sample data against the rule.
Sources
Related terms
- Data schemaA data schema describes the structure and rules of data. It defines fields and data types, for example; provenance and freshness are additional questions.
- Schema registryA schema registry centrally manages data schemas and their versions. Compatibility checks help data exchange but do not replace checking meaning.
- Transactional inboxA transactional inbox uses durable message records to protect local processing against duplicate deliveries.
- Message acknowledgementA message acknowledgement tells the broker that a delivery has been received or processed according to the agreed rule.
- Retry jitterRetry jitter varies waiting times randomly to spread retries and reduce simultaneous requests from many clients.
- Test tenantA logically bounded customer context of a multitenant application, configured for testing.
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