• AI Projects with practical Experience

Only the business-partner counts (not only) in the business domain of RealEstate

Only the business-partner counts (not only) in the business domain of RealEstate

Project Profile

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

DurationFrom 11/1/2020 to 12/1/2020 with about 1 months of full engagement
Data and ToolsMarket - RealEstate
 •SAP R3 Export (DEB/KRED - Tables)
 • Custom-DatawareHouse (DWH)
 • Optional: DataScrapping Google API/Places/Content
 • Optional: Different International Service Data Provider (Paid/Free)
IntegrationDataExchange with Excel/XML for Data Migration
AI Methods • Deep Learning
 • Heuristics

Engagement Use-Case

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 Approach

AI key technology used in our solution"String Distance Algorithm" works already with few samples as backup for NLP approach.
Solution ApproachNLP Deep-Learning Heuristics
Project ApproachSimply agile
Project TypeProof-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