Tamr helps enterprises improve the ROI of their move to SAP S/4HANA® by enabling an automated, ‘quality-first’ approach to data migrations. Raw sources are validated, mapped, mastered, classified, and published to SAP S/4HANA® with 80% less human involvement than traditional approaches. End-users get richer, more complete data in less time with Tamr.
Deliver Business Results
Automated the migration of 10M+ attributes across 100k+ source tables; delivered analytic-ready data within three months
Enabled millions of dollars in new sales opportunities by providing a 20x improvement in the efficiency of integrating product master data
Driving sales opportunities with compete customer records generated by migrating to a single SAP technology from multiple ERP` systems
“By using Tamr, by the time the companies we’ve acquired are ready migrate to SAP, a big portion of the data cleanup work will be done and that’s a huge win for us.”
Senior Vice President of Digital Transformation,
Accelerate adoption of new infrastructure by powering it with clean, complete data across business domains
Reduce migration risk by automating long lead-time processes such as data mapping
Save money on human-intensive processes such as data cleaning, deduplication, and classification
Lay the foundation for better process management by integrating data sources beyond ERP
Solutions To SAP S/4HANA® Migrations At Scale:
Tamr enables more successful migrations through a structured five-step process of validating, mapping, enriching, mastering, and publishing raw source data to SAP S/4HANA®. Machine learning is relied on heavily to learn from previous ERP implementations & minimize human effort for tasks such as:
Schema mapping: After connecting to the raw sources, Tamr profiles and validates the data. Once completed, machine learning automatically recommends mappings from the sources to user-defined schemas, saving countless hours manually aligning source to target.
Data Quality & Enrichment: Once aligned to the user-defined schema, the quality & completeness of individual attributes is measured. Values are standardized and enriched using a Tamr-managed library of dozens of sources to ensure target systems are being loaded with accurate, verifiable data.
Record mastering: Tamr establishes relationships between records referencing the same entity, forming the basis for golden records which are published into the target system. Tamr’s patented human-in-the-loop process ensures data is mastered in a way that meets the needs of the new environment, and delivers 20%+ more accurate results with 80%+ less human effort versus traditional, manual-intensive approaches.