Only the business-partner counts (not only) in the business domain of RealEstate
Proof for the aggregation of debtor/creditor data in the context of a system migration from SAP R3 to SAP S4/Hana.
Data aggregation for migration risk reduction
At a glance - essential project data
|Duration||From 11/1/2020 to 12/1/2020 with about 1 months of full engagement|
|Data and Tools||Market - RealEstate |
•SAP R3 Export (DEB/KRED - Tables)
• Custom-DatawareHouse (DWH)
• Optional: DataScrapping Google API/Places/Content
• Optional: Different International Service Data Provider (Paid/Free)
|Integration||DataExchange with Excel/XML for Data Migration|
|AI Methods|| • Deep Learning|
Duplicate cleansing for accounts receivable and accounts payable in S4/Businesspartner.
Client motivation / Solution aims.
- Reduction of the cleanup effort for business partners in a time-critical project
|AI key technology used in our solution||"String Distance Algorithm" works already with few samples as backup for NLP approach.|
|Solution Approach||NLP Deep-Learning Heuristics|
|Project Approach||Simply agile|
|Project Type||Proof-Of-Concept (POC)|
|ML Integration and ML Operations|| • Operation Integration|
• Excel Import
• Quality Reporting of Summarization/Merge
Insights and Details
Starting from Excel Export of the Customer Datawarehouse. Reaching Reductions of about 90%. A small Visualization shows the Clients Distribution of his own Debitors/Creditors to be summarized