Automated data cleansing:
Housekeeping in SAP S/4HANA – keep the size of your database under control
 

If you have already taken a look at SAP S4/HANA, are thinking about a conversion or are even already working with it, you will have noticed the crucial difference between this current SAP version and its predecessors. SAP S/4HANA works on the basis of an in-memory database. This means that all data is held in main memory, which makes it much faster to process. And this is also necessary, as almost all queries and applications are becoming increasingly data-intensive. In our blog post "SAP S4/HANA - Why actually?" you can read details about the in-memory way of working and why it makes sense.

However, this architecture also has its pitfalls: Main memory is significantly more expensive than conventional hard disk storage or SSDs. At the same time, the amount of data is constantly growing - so considerable costs add up quickly. If you operate your SAP system in your own data center, this means that you have to dimension your IT resources generously at the beginning or regularly increase main memory. Even the cloud cannot solve this problem because as data volumes grow, you need more cloud resources. Although these can be added flexibly and easily, they naturally also cost additional money. With RISE with SAP, SAP offers a complete package that significantly simplifies the move to the cloud - but here, too, the costs depend on the scope of the application and its data.

Reduce data volumes: especially useful before a conversion

How can the size of the database be kept in check? Regular, systematic SAP housekeeping is an effective tool for this. It is a simple method for ridding your system of useless data and limiting the size of your database. SAP housekeeping, which should be an integral part of every SAP operation, involves identifying, archiving or deleting data that is no longer required (this is also referred to as data reorganization).

It is particularly advisable to carry out housekeeping before a conversion to SAP S4/HANA - because the less data that needs to be migrated, the better. SAP's Readiness Check not only recommends preparatory measures that you should still take, but also shows you the data that you should take a closer look at. In most cases, these are essentially the 100 largest tables stored in the database. With the help of a time-based analysis, you can see the age structure of the information.

The half-life of data

In principle, a distinction can be made between two basic types of data.

• Temporary tables: They are created within process steps during processing. Typical examples are spool files (e.g. TST03), RFC logs (e.g. ARFCSDATA) and application logs (e.g. BALDAT).
• Application data: This is mass data with high storage requirements, usually the result of several interdependent process steps. Typical examples are costing data, MM follow-up posting data, and individual financial and controlling documents. 

Temporary data can often be deleted, especially if it has exceeded its retention periods or does not need to be retained at all. Application data, on the other hand, is often subject to longer retention periods. Thus, while they must be kept available, they do not need to be available for current queries and processes. They can be archived and thus removed from the main memory.

Keep performance high and costs low

Especially if you are preparing the conversion to SAP S4/HANA, we recommend that you perform SAP housekeeping. Experience shows that this can significantly reduce the migration effort and the costs incurred later for the main memory.