What is data mapping in CDX and how is it used in integration?

What is data mapping in CDX and how is it used in integration?

• A. Data mapping links source fields to target fields; used during schema alignment in ETL/ELT to translate data.
• B. Data mapping describes user permissions mapping to roles.
• C. Data mapping is about mapping memory addresses; used in hardware.
• D. Data mapping is only for database migrations; not used in integration.

Answer: (D)

Data mapping in CDX is the process of defining how each field from a source dataset corresponds to a field in a target dataset. In integration, this acts as the translation layer so data from different systems—often with different field names, types, or formats—can be aligned to the destination schema. During ETL or ELT workflows, the mapping specifies which source field feeds which target field and what transformations to apply (such as type casting, format changes, or value concatenation) to maintain consistent data quality. This alignment enables data from multiple sources to be combined and analyzed together, ensuring downstream applications receive data in the expected structure and semantics. Other ideas like permissions mapping, memory addressing, or limiting mapping to migrations miss the core role of mapping data fields across systems for seamless integration.

Data mapping in CDX is the process of defining how each field from a source dataset corresponds to a field in a target dataset. In integration, this acts as the translation layer so data from different systems—often with different field names, types, or formats—can be aligned to the destination schema. During ETL or ELT workflows, the mapping specifies which source field feeds which target field and what transformations to apply (such as type casting, format changes, or value concatenation) to maintain consistent data quality. This alignment enables data from multiple sources to be combined and analyzed together, ensuring downstream applications receive data in the expected structure and semantics. Other ideas like permissions mapping, memory addressing, or limiting mapping to migrations miss the core role of mapping data fields across systems for seamless integration.