Data quality & cleansing
Know the quality of your data. Fix what matters.
Configure quality rules, run scheduled checks and follow scores over time. Every issue reaches the business owner who can resolve it, and every correction is staged before it is loaded.
Bad data rarely announces itself.
Duplicate customers, incomplete materials and inconsistent vendor records slow down operations, reporting and every migration or AI project that depends on them.
Most teams find out when something breaks. And when they do, the people who found the problem are rarely the people who know the right value.
What changes with DATAshaper
- Data quality becomes a measured number, overall and by domain
- Issues reach the people who can resolve them
- Corrections are reviewed and staged, not pushed blindly
How DATAshaper helps today.
Configurable rules
Express what good data means for each dataset, entity and domain.
Scheduled checks
Recurring checks measure quality continuously instead of once a year.
Scores and trends
Follow a quality score overall and per domain, with dashboards that show the trend.
Named owners
Assign each issue to the business user who knows what the right value is.
Collaboration in Studio
Owners investigate, comment, edit and set statuses in DATAshaper Studio.
AI-suggested corrections
AI proposes values for issues your rules found. People approve them, or you configure controlled automation.
Your source systems stay untouched.
Approved corrections are prepared in a separate staging table. Nothing is written straight into your ERP.
Your own loading process, or an integration you approve, moves the staged changes into the target system.
- Source systemLeft untouched
- Staging tableApproved corrections
- Target systemLoaded by your process
Data quality in practice.
Bruker measures the quality of its SAP data ahead of S/4HANA. At mateco, quality checks run inside a global ERP migration.
Building a data quality foundation for SAP S/4HANA.
Rules configured, measurements underway
Making a global ERP migration predictable.
Rollout in progress
Questions about data quality.
Do we need a migration project to use it?
No. Bruker uses DATAshaper to measure the quality of its existing SAP data, ahead of a future S/4HANA migration.
Can our own team maintain the rules?
Yes. After a one-week training, Bruker’s team configures rules and runs measurements largely on its own, with support available on demand.
Does DATAshaper alert us when quality drops?
Notifications and threshold alerts are in development. Today, scheduled checks and dashboards show how scores and trends move.
Ready to take control of your data?
Whether you're preparing for AI, improving data quality or planning an ERP transformation, start with a conversation.
Talk to an expert
Bring a specific challenge and discuss it with someone who has solved it before. Book a time or send a message.
Book a demo
See the platform in a guided session, usually with representative sample data. Book a time or send a message.