System Optimization using SAP S/4HANA’s Data Aging
Step-by-step Data Aging Implementation Process
Meet the Authors
There has been a significant increase in data generation owing to enhanced usage of applications and increasing digitization of business processes. To derive true value from the data, this has to be stored and processed efficiently. The larger the quantity of data, the more complex it is to sift through to gain insights. This is especially so with real-time analytics being run directly on top of transactional systems.
SAP S/4HANA, true to its capabilities, facilitates faster transactions while enabling equally fast reports to run on top of these transactions. However, there needs to be a well-designed approach to ensure efficient data storage/bifurcation to ensure the right amount and category of data is stored in memory and remains in disk, which strikes a balance between runtime availability of data and cost of infrastructure for data storage in memory. To facilitate this, Data Aging should be implemented.
This article enables the readers to understand:
– The concept and benefits of Data Aging, with steps to implement it.
– Temperature segregation of data into Hot and Cold data.
– Step-by-step process to segregate data effectively.
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