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DataOps

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DataOps is an automated, process-oriented methodology, used by analytic and data teams, to improve the quality and reduce the cycle time of data analytics. While DataOps began as a set of best practices, it has now matured to become a new and independent approach to data analytics. DataOps applies to the entire data lifecycle from data preparation to reporting, and recognizes the interconnected nature of the data analytics team and information technology operations.

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dataops-testgen

DataKitchen / dataops-testgen

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DataOps Data Quality TestGen is part of DataKitchen's Open Source Data Observability. DataOps TestGen delivers simple, fast data quality test generation and execution by data profiling,  new dataset hygiene review, AI generation of data quality validation tests, ongoing testing of data refreshes, & continuous anomaly monitoring

python data-science data postgresql snowflake self-hosted data-engineering dataops mssql redshift data-quality dataquality datavalidation data-testing dataprofiling data-observability datachecker
  • Updated Feb 25, 2026
  • JavaScript
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Website
github.com/topics/dataops
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open-data