![]() "It must be easier", this sentence at one of our team meetings was at the beginning of the development of the dynamic data extraction.ĭab:Exporter: reliable, but time-consuming in package management We and our customers describe them as "export or download packages" - the definition of the respective quantity of SAP data to be extracted.įor many years, we had to manually create these export packages for our customers so that they could extract the desired data from their SAP system and analyse it in ACL for Windows or Robotics. The type and scope of this metadata depends on the questions to be analysed. ![]() This definition contains metadata in the form of a list of tables or table fields, in combination with filters to be applied during extraction. If you want to carry out evaluations on SAP data with an external analytics tool, you must define in advance which raw data are to be extracted from the SAP system as a basis for this. In fact, the idea for one of the greatest improvements of the dab:AnalyticSuite came from a spontaneous idea. We could say we went to work with a well thought-out plan and optimised our processes quite strategically. Dynamic Data Extraction The evolution of one-click data export
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