The open source architecture of the SAP Financial Services Data Platform (FSDP) favors the flexible integration of a wide variety of source systems and data. On the one hand, this approach offers a high degree of flexibility. On the other hand, however, the need for powerful data quality management is also increasing in this context in order to meet the demand for high-quality data on the platform. After all, the data flows into analytical business reports, which are ultimately used as a basis for important corporate decisions.
Approaches and starting points for quality assurance
There are two approaches to ensuring data quality. In this way, data quality can be assured either during or after the data loading of SAP FSDP.
Quality assurance before data loading should be taken into account in any case, as this prevents inconsistent data records that do not comply with the specifications from entering SAP FSDP in the first place. Any downstream error analyses and corrections can thus be reduced to a minimum.
However, a functioning solution for data corrections after loading is just as important and should be considered to ensure that corrections can be carried out easily, with various check mechanisms and in an audit-proof manner.
In the end, the balanced combination of both approaches makes for good data quality management – and not just in SAP FSDP.
Early integration of data quality management pays off!
Thinking about implementing high-quality data quality management early on is worthwhile in any case. If a functioning data quality management is already established during the implementation of SAP FSDP in development and test landscapes, everyone will already benefit during the integration of the first source system. This is because the mapping of the data, the dependencies of data records and the business logic can already be checked during the first – even incomplete – delivery to SAP FSDP! And that from the very beginning.
Most implementation or integration projects proceed in such a way that the first data breakthrough is tested fairly quickly. Then it waits until the data is “good enough” before loading it into the accepting system. And only then are they checked – for the most part manually – by the testers.
With a solution that, like SAP FSDP, can also handle fewer or incomplete data records, the test can be brought forward significantly and the errors can be listed automatically. So that later on, the testers are not concerned with the data quality per se, but only test what a “human tester” is needed for, e.g. when assessing the technical results.
We have used our knowledge to develop a fully comprehensive solution for optimal data quality management for SAP FSDP. Read more here about the ADWEKO data platform manager for SAP FSDP.
Damian Seehrich has more than 10 years of experience in software engineering. His main focus is on the design and development of applications and interfaces using SAPUI5, SAP HANA and ABAP Objects. But technical consulting is also part of his job. Currently, Damian Seehrich is responsible for the technical implementation of a standardized interface between SAP FSDM and Wolters Kluwer’s OneSumX in the role of development manager.
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