CUTO · SAP Transformation Management
Clean data. Safe go-live. No last-minute surprises.
Data quality problems are the leading cause of SAP go-live delays. CUTO's Data Management app gives you full control over migration planning, validation, and harmonization — so issues get caught before they become blockers.
Why data migration derails so many SAP projects.
Source data sits across multiple legacy systems. The data quality picture is unclear until the extraction runs. Duplicates show up in the staging environment two weeks before go-live. Validation failures spike. The cutover window is at risk.
Meanwhile, the migration team is managing everything in spreadsheets — manually tracking which objects are ready, which aren't, and who's responsible for fixing what.
It's a known problem. It happens on nearly every SAP project. And it's entirely preventable with the right tooling.
A central catalog of every data object that needs to move — tracking source system, migration approach, responsible team, and current status. Full mapping documentation in one place, not spread across ten spreadsheets.
Migration Catalog & Mapping
Validation Engine
Automated validation rules run against your source data before migration. Errors are categorized by severity — blocker, warning, or informational — with a real-time dashboard showing pass rates per data object. Find problems early, when they're still cheap to fix.
Data Harmonization — Deduplication
Intelligent duplicate detection using fuzzy matching. Side-by-side comparison lets your team review potential duplicates and select the Golden Record. A 4-eyes approval workflow ensures nothing gets merged or deleted without proper sign-off.
Reconciliation & Quality Gates
End-to-end reconciliation between source and target: count matching, value matching, completeness checks. Full audit trail for compliance. Every go-live sign-off has documentation to back it up.
Integrated with Project Management
Data migration tasks and quality gates link directly to the project plan. When a blocker appears in the migration catalog, it surfaces automatically in the project risk register. Nothing falls through the cracks.
How It Works
Step 1: Catalog your data objects
Identify what needs to move, from which systems, using which migration tools. Document mapping logic. Assign ownership. Everything tracked in one place from day one.
Step 2: Assess source data quality
Run validation rules against your source data early in the project. Understand the quality picture before you're deep into the Realize phase.
Step 3: Cleanse and harmonize
Deduplicate with fuzzy matching. Define Golden Records with 4-eyes approval. Ensure the data you're migrating is the data you actually want in S/4HANA.
Step 4: Migrate and validate
Execute migration runs and validate results against your defined quality criteria. Track pass rates per object, per run, per cycle.
Step 5: Reconcile and sign off
Final reconciliation between source and target. Count checks, value checks, completeness verification. Sign-off documented and traceable. Go-live cleared.
Related Apps
- → /products/test-management/ — Datenqualität im Testing bestätigen
- → /products/process-house/ — Prozesse als Grundlage der Datenzuordnung
- → /solutions/use-cases/data-migration/ — Use Case: Datenmigration
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