Data model transformation is a core service function that can be performed by proven technologies that have been around for years. Therefore, it is recommended that you look for opportunities to…

Question

Options

• ATrue
• BFalse

• A
  27% (9)
• B
  73% (24)

Explanation

B is correct because while data model transformation is indeed a mature, proven capability, recommending its use "wherever possible" - particularly in larger, more complex service compositions - contradicts sound architectural guidance. Overusing transformation introduces unnecessary overhead, latency, and maintenance burden, and in complex compositions these costs compound, increasing fragility rather than reducing it. The principle is to minimize transformation by designing toward canonical or standardized data models, reserving transformation only where genuinely required.

Option A is wrong because it conflates "proven technology" with "should be used liberally." A technology being reliable does not make it advisable to inject it throughout a service landscape; indiscriminate use of even good tools degrades overall design quality.

Memory tip: Think of data model transformation like a translator at a conference - necessary when languages differ, but hiring one for every conversation when a common language exists wastes time and adds room for miscommunication. The goal is fewer translations, not more.

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