Delta loading of data is a fundamental concept that plays a crucial role in time series approaches, particularly when managing various data sources without natural keys or dealing with system changes. By employing delta loading, businesses can reduce dependency on technical issues and concentrate on data aspects directly relevant to their operations.
In essence, delta loading involves flushing and re-inserting a portion of time series data between minimum and maximum dates. This process can be efficiently managed through various scheduling parameters. Within MAIS, there are several delta loading modes available:
Relative Mode: Allows specifying a number of days backward or forward from the current date.
Static Mode: Enables setting a fixed delta range from one date to another.
Dynamic Delta Detection: Automatically determines the date range based on the source's minimum and maximum dates.
SUMMARY
Additionally, combinations of these modes are feasible, providing flexibility for different scenarios. For instance, data may need to be flushed further backward if a source system undergoes reconfiguration. Through delta loading, changes in data can be securely managed, granting the data team direct control over the process.
With numerous possibilities available, delta loading ensures adaptability to diverse situations, empowering businesses to efficiently manage their data operations.