Learn about the top 5 drivers for data archiving and what questions you need to consider in order to improve the performance of your SAP environment, optimize costs, and more.
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Learn about the top 5 drivers for data archiving and what questions you need to consider in order to improve the performance of your SAP environment, optimize costs, and more.
For some, the idea or suggestion of data archiving can be unsettling. We are so used to having lots of information at our fingertips. It feels like a comfort to have several years of data that can be referenced whenever needed. Thus, when the subject of archiving production orders or sale orders arises, it is often met with resistance. We believe this information is not just a want, it’s a need. We may need that sales order or production order from 10 years ago.
However, in today’s SAP environment, there are several drivers that compel us to revisit the subject of data archiving:
As we delve into the concept of archiving, it is essential to recognize that this is not solely an IT decision. It primarily requires the involvement of the business or data governance to drive the decision, while IT executes the plan. For example, here are some questions to consider:
To clarify some definitions:
Many companies have not established retention policies. A retention policy outlines the governance rules for data retention periods. After the data’s designated lifespan, should the information be retained in an archive, or can it simply be deleted? Retention periods are often measured in years. For example, finance data needs to be kept for 7 years to comply with GAAP record retention policies. After 7 years, what should happen to this information? Should it remain online, or should it be moved to an archive? What about non-financial information? Does it have a shorter life, such as 4 years? Additionally, information like system logs, EDI transactions, or temporary system movements may only be relevant for a few months before becoming data occupying valuable storage space. Reporting also plays a critical role in retention policies since some reports rely on specific information. Consider moving less critical information to a data warehouse for long-term reporting purposes.
Now that you have these ideas in hand, how do you get started? First, consider the drivers leading you towards data archiving. Set goals based on these drivers and determine what you want to accomplish with data archiving. Then, conduct an assessment of your system to identify areas with the highest data usage and storage. This assessment will highlight where the largest amount of data resides in the database.
With a good plan in place, you can start to recognize better system performance, cost reduction from reducing the size of database and cleaner information in the database.