Temporal Tables
Temporal Tables are useful in scenarios that require tracking of data changes in a database environment
Temporal Tables are useful in scenarios that require tracking of data changes in a database environment
Use cases for temporal tables include any of the following scenarios:
Use temporal system-versioning on tables that store critical information for which you need to keep track of what has changed and when, and to perform data forensics at any point in time.
Unlike a data audit, where the focus is typically on changes that occurred to individual records, in time travel scenarios users want to see how entire data sets changed over time.
Anomaly detection is the identification of items that do not conform to an expected pattern or other items in a dataset.
Dimensions in data warehousing typically contain relatively static data about entities such as geographical locations, customers, or products.
You can rely on historical data in system-versioned temporal tables to quickly repair individual rows to any of the previously captured states.
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