Ways of SAP system copy: export / import
Conclusion
Suitable tools make it possible to automate and accelerate the necessary creation of true-to-original SAP system copies, for example. This means that you have all production data available on your test system in a short time.
A non-production SAP system should also have the same repository status as the source system, regardless of the data transfer method chosen for the refresh. All the data that makes up an SAP system is stored in the repository. This includes, among other things, the definitions for the database fields and tables for master and transaction data.
Challenges with SAP system copies
Advantage of the system copy: Users receive one hundred percent consistent test data. A disadvantage, however, is the high storage space requirement of such a test system, which corresponds to that of the productive system. In addition, an authorization concept for the system copy is required to protect the authentic data it contains. Otherwise, company secrets are at risk, and there is a violation of regulations such as the Federal Data Protection Act and the Sarbanes-Oxley Act.
Partial copies from SAP systems with the help of tools open up potential savings and in many cases make system copies and complete client copies superfluous. The ability to anonymize data reduces the effort required to comply with data protection regulations in training systems, for example. In addition, up-to-date, consistent test data improves the flexibility and quality of development and test environments. Users save money through reduced resource requirements.
To shorten the list of activities and to simplify the complete process of a system copy or a system refresh and to save manual activities, you can use "Shortcut for SAP Systems". Several manual activities can be omitted because with "Shortcut for SAP Systems" the system-specific data can be saved before the copy and imported again afterwards - also automated. This reduces the error-proneness that is inevitably caused by manual activities and enormously reduces the time span until the system is available again.
Larger productive systems, on the other hand, are not so easy to virtualize.
Large or complex tables with an extremely long runtime can lead to a very long total runtime, even if a separate package has already been defined for the table.