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Don’t Be Scared to Delete Data – Tips for Shrinking Your SAP Database

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What are the biggest challenges with running SAP data management projects?

 

I’d name 3 things: data growth, low visibility, and reluctance to delete data. Data growth goes together with the growth of the company and expanding its scopes. From our experience with complex SAP landscapes, we know that an average system grows by 35%-40% annually. Every 1 TB of SAP productive data is replicated 7 times in the SAP landscape (due to system copies and backups), which calls for a bigger and more expensive storage space. And that gives sleepless nights to those who plan migration to SAP HANA.

 

 

Lean data management system growth

 

 

Low visibility means that organizations often do not realize the potential of data management and possible cost savings. During my 8 years of work on various projects, I’ve learned that the average SAP BW system can be reduced by 30%, which does not only save costs but also improves performance of the system.

 

The last challenge is the reluctance to delete data that we see in our SAP customers. I’d like to debunk some myths that surround data deletion – it is possible to restore deleted data, just as much it is possible to report on and change archived data. And to stay on the safe side, we recommend our customers to identify which data they are using and which data is never accessed. In this way, housekeeping and archiving can be performed without testing your nerves.

 

hot warm cold data in sap system

 

 

What does a data management project look like?

 

The goal of every data management project is to balance the value of data with the costs that it generated. A project can last from 2 months up to a year, depending on the customer’s requirements.

 

Typically, we kick off with a Fitness Test that checks the health of the SAP system. It helps us to get a detailed diagnosis of the system’s pain point and reveal the potential for housekeeping and archiving.

 

Then, we recommend to verify which data is old and ready to be archived. But we don’t stop there – we also check which data is hot, warm, and cold. This means that we can view what is the actual data usage, which data is important to SAP users and which can be safely moved to a nearline storage (or another database). Finally, we run automated archiving and/or housekeeping and enjoy the weekend, before we run off to another project.

 

 

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