Versioning
Data Versioning is a technique used in data management to track changes made to data over time. It involves creating and storing different versions of data, allowing businesses to access and analyze specific versions whenever needed. Data Versioning ensures data consistency, traceability, and provides a historical record of changes made to datasets.
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Data versioning is the practice of keeping track of changes made to a dataset over time, each version of the dataset is saved and can be accessed at any time.🔗Dagshub -
Maintain a history of changes to data for auditing and tracking purposes.🔗dagster.io -
Data versioning makes it easy for data consumers to repeat a process or research, compare outputs as a result of using different data versions.🔗dzone.com -
https://en.wikipedia.org/wiki/Data_Version_Control_(software)🔗en.wikipedia.org -
What is data versioning? When is data versioning appropriate? We review the various tools and use-cases needed for the best implementation.🔗Git for Data - lakeFS -
Data Versioning is a practice that involves keeping track of changes made to data over time, allowing businesses to easily access and analyze different versions of their data.🔗dremio.com -
Data versioning is when different versions of the same data are kept in different places, based on when it was made and how it was changed.🔗Pachyderm