The importance of data monitoring
As data volumes and managed data entities grow, so does the complexity. Many organisations still rely on manual data validation, which is fast becoming unsustainable as environments continue to evolve at pace. This can result in bad and unknown data slipping through undetected, which can both increase operational risk and erode data quality and understanding across environments.
Without robust monitoring capabilities, enterprises often depend on manual tracking, or worse, no tracking at all. A lack of traceability makes it hard to detect when schema changes occur or understand their impact, leaving sensitive or regulated data exposed to compliance breaches and security vulnerabilities.
Common signs of poor data monitoring in your enterprise include:
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Reactive teams forced to spend time on maintenance and repetitive tasks, such as re-validating data after every change.
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High failure rates due to poor quality test data and late detection of data issues, resulting in costly bug fixes at later stages of development.
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Long feedback loops caused by schema inconsistencies between environments and outdated, incomplete or poorly covered test data.