Data growth remains one of the top challenges of SAP systems administrators. Our experience in working with various SAP environments shows that even up to 40% of your system can be freed up by archiving or deleting temporary data. For the best results, follow our 5 Principles of Lean Data Management:
1. The cost of storage needs to match the business value of your data.
The key to data management is to understand how much VALUE does your data generate. The COST of the storage then should follow its value. Choose the best storage technology according to the required speed of access, speed of data insertion, the total costs of the storage that fits to the value of data. In the SAP environment this decision is to make to pick from technologies such as SAP HANA, Hadoop HDFS, Hadoop HIVE, BWA, ORACLE, DB2, DB2 BLUE. MS SQL, SAP IQ, file server, cloud and more. Which one is your choice?
2. Separate Data Management from Storage Technology.
An open architecture secures your current and future investments. Based on the storage costs your today’s choice for archive storage could be ORACLE or MS SQL. Think about your future landscape – possibly SAP HANA and HADOOP data lakes storing your BIG DATA. It would make sense to use the same archiving software which would allow to migrate your archived data to any other database technology. Does your current archiving solution support multiple storage types?
3. Automation and central rules ease Data Management.
AUTOMATION is the KEY. When it comes to saving implementation effort for archiving look for an archiving solution that supports and enables automation. This includes bringing same type of objects together in groups which would share same retention, set up activities and executed together. When you think of data management in complex SAP landscapes CENTRAL rules and scheduling is important. This will but ease your operation time so that you can focus on innovation.
4. Iterate through the DMAIC cycle several times.
DMAIC – Define, Measure, Analyze, Improve, Control. Refine rules based on actual data usage statistics. The best practice of data management follows the hot, warm and cold definition of data temperature. Once you understand which data is used by SAP users in reporting this can help you to refine your retention rules. Do you run operational intelligence to understand your user behavior?
5. Start reducing data volumes from bottom (staging) to top (reporting).
First start with the analysis. Be aware if your data management potential sits in the temporary data of outdated business data. The first would call for housekeeping (deletion) and the second for archiving (move data to a cheaper storage). Do you know the amount of your SAP housekeeping data, Changelog, PSA data, DSO, WDSO, Info Cube data?