Only 34% trust synthetic data’s referential integrity — and it’s holding adoption back
While enterprise leaders overwhelmingly believe in the promise of synthetic data, adoption lags. As a result, synthetic data has great, The post Only 34% trust synthetic data’s referential integrity — and it’s holding adoption back appeared first on The New Stack .
Despite enterprise leaders' strong belief in synthetic data's potential, adoption remains limited. A primary reason? Only 34% of leaders trust synthetic data to preserve referential integrity, according to Perforce Delphix research. This lack of trust is holding back widespread adoption.
While enterprises recognize synthetic data's benefits in safeguarding sensitive information, accelerating development, and expanding data access responsibly, the issue lies in data quality. Only 38% of leaders believe synthetic data delivers sufficient realism.
The limited usage of synthetic data within software engineering and testing teams can be attributed to this trust gap. Synthetic data must reflect the intricate relationships across diverse databases and systems, mirroring real-world behavior. Otherwise, teams risk testing isolated components instead of genuine business processes.
To unlock synthetic data's full potential, organizations must prioritize maintaining realism and relationships. This involves generating data that adheres to expected formats, ranges, and business logic, and continuously evaluating data quality as systems evolve. With trustworthy synthetic data, enterprises can accelerate development while maintaining stringent privacy protections.
Written by urgent.news from The New Stack's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
