1. Data Volume: — SAP ERP is generally chosen by large multinational companies transacting thousands of documents each day. Data needs to be analyzed, but huge amounts of data make it difficult to perform advanced analytics for audit purposes.
2. Extracting data from the SAP system: — Extracting audit-based data from the SAP system is not easy. Manual data extraction through T-code SE16 is also not a feasible option. It allows us to extract one table at a time which increases manual tasks. To address it, we have developed an automated solution.
3. Table & field name in the German language: — SAP is a German company and all the tables and fields names are available in the German Language. To better understand data you should have basic knowledge of the table & field description. Although SAP gives you the option to see fields in the English language. For data mapping, it is good to know the original field name.
4. Data mapping between SAP Tables: — SAP contains more than 10,000 tables with predefined names and fields. After data extraction, the most complex job is to understand and implement the same data mapping for audit purposes.
Business Data Analytics ~ Data Warehousing ~ Automation Solutions ~Digital Transformation ~ BI ~ Visualization ~ ML. https://www.linkedin.com/in/priyankauppal/