𝗔 𝘄𝗲𝗹𝗹-𝗱𝗲𝘀𝗶𝗴𝗻𝗲𝗱 𝗱𝗮𝘁𝗮 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗰𝗮𝗻 𝗲𝘅𝗽𝗹𝗮𝗶𝗻 𝗶𝘁𝘀 𝗼𝘄𝗻 𝗿𝗲𝘀𝘂𝗹𝘁𝘀.

When an output seems unexpected, developers should be able to trace the source inputs, transformation rules, validation results, and processing sequence.

That trace makes it easier to identify whether a problem began upstream or emerged during application processing.

Useful records also support repeatable tests and clearer incident reviews.

This is especially relevant when data influences actions that are difficult to reverse.

Explainable processing is not a luxury; it is a practical tool for maintaining dependable systems.

@WinkLink_Oracle
@Justin Sun孙宇晨

#TRONEcoStar