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Data Quality Initiatives

A strong foundation for your data.

Enhance your data quality foundation for your business with the MetaCenter® platform.  Metadata management capabilities support quality improvement as they give insight into where bad data is coming from, how it’s being used, and who can fix the problems.  Search and drill down into metadata to validate data definitions, business rules, data ownership, security controls, and physical data structures.  Get quality right.

How MetaCenter® Helps with Data Quality Initiatives

 

Document Your Quality Requirements

Keep track of data quality requirements by documenting them directly in the metadata.  The MetaCenter® metadata repository is highly customizable and extensible, allowing you to perfect the way your business and technical personnel store and access data quality requirements.

Prevent Errors at the Source

Begin every project that creates or changes data with a review of business context, term definitions, existing data assets, and quality requirements.  The MetaCenter® platform helps your staff design systems and data flows to a higher quality standard.

Respond Quickly to Problems

Event and threshold driven alerts notify data stewards when quality problems first appear in your operational metadata.  This supports fast data quality incident response and effective problem management.

Find & Fix Errors with Precision

When problems emerge, confirm the root cause with certainty.  MetaCenter® object relationship reports and data lineage analytics allow your quality teams to examine data flows and eliminate sources of bad data.

 

Benefits of MetaCenter® in your Data Quality Initiatives

 

Multiply Cost Savings with a Preventative Quality Posture

Leverage your metadata during up-front analysis and planning to prevent systems from breaking. Systems built with accurate data requirements can lower a Total Cost of Operation lower by a factor of 10.

Save Time & Effort Managing Data Quality Problems

MetaCenter® metadata analytics tools allow you to quickly pinpoint sources of data quality problems, leading to faster response and resolution.  Solve problems with less people and fewer unanswered questions.

Increase Trust in Your Data

Eliminate quality concerns stemming from confusion, miscalculation, or data duplication.  Stop questioning the validity of your data and starting putting your data to work for your business.

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