August 26, 2020 Where does your data relevant to the GDPR actually reside?
SAP® landscapes consist not only of production environments but also of staging environments. Filling these development, quality assurance (QA), test systems creates complexity and repetitive, monotonous activities: for appropriate and consistent testing and acceptance of changes in programmes and processes, SAP recommends a special approach with the "homogeneous system copy" to provide non-production systems with up-to-date data.
Typically, this procedure involves a large number of manual activities. Depending on the structure and size of the systems, these can last from hours to several days. If there are also environments of several connected systems, these times add up to really painful downtimes in the context of a landscape copy. Thus, there is actually never "the right" time for this. In addition to the unavailability of the target systems for operating and project teams, system and landscape copies block other important and, last but not least, expensive resources: internal or external SAP Basis professionals.
Libelle SystemCopy (LSC) is a software solution for fully automated and optimised SAP system and landscape copies. With the proverbial push of a button, you update QA and test systems with fresh production data. Because Libelle SystemCopy…
Read more about the background of LSC in this whitepaper.
With the entry into force of the EU General Data Protection Regulation (EU GDPR), however, the topics of data protection and anonymisation are increasingly coming into focus. The basic regulation regulates Europe-wide minimum standards that can be further tightened regionally. This influences the handling of sensitive data in companies. Especially those IT environments are now coming into focus in which access to sensitive data is only restricted to a certain extent: development and test systems. In order to adequately counter the risk of unintentional data access and data leakage here, data sets should be pseudonymised according to the regulation (Article 4.5). Pseudonymisation is per se reversible, however, and enables a conclusion to be drawn about original data. Anonymisation of data sets goes one step further towards irreversibility.
Whichever variant your company decides on: in order to meet the objective of the test systems, pseudonymised or anonymised data sets should also depict logical relationships. Otherwise, statements on process quality, continuity and logical correctness of business processes within IT environments are only reliable to a limited extent.
Libelle DataMasking (LDM) (LDM) enables the anonymisation and pseudonymisation of critical data in QA and test systems, taking logical relationships into account. LDM works independently of the business applications used, on individual systems and in complete system landscapes. The result is anonymised, consistent data for the development and testing of software and business processes across all platforms. The anonymisation methods used deliver realistic, logically correct values for your test systems, with which almost all business cases can be described and tested. Libelle DataMasking supports data sets in SAP and non-SAP systems holistically and across systems. And LDM integrates seamlessly with LSC.