SAS® Data Quality for Midsize Business

Get accurate, reliable and consistent data.

Assess, improve, monitor and manage the quality of all your data, structured and unstructured. Designed and priced for small and midmarket businesses, our easy-to-use solution is suited for both business and IT users. It's available in both desktop and client/server versions, so you can start small and grow as your needs change.

 

Benefits

Get a complete, accurate and unified view of data.

The solution connects disparate technology systems and streamlines information transfers to give users a precise, comprehensive view of all data – structured and unstructured. An automated early-warning system flags out-of-tolerance data.

Mitigate risks and reduce costs.

Industry-leading data profiling, data quality and entity resolution technologies help users assess the scope and nature of data quality problems across multiple systems and sources. Consistent standards and business rules reduce or eliminate costs of duplicate or incorrect data storage and administration. A consolidated portfolio of capabilities from one vendor minimizes licensing, integration, maintenance, training and support costs.

Make faster, accurate decisions.

Through a common, shared interface, IT and business users collaborate to define centrally maintained business rules, data definitions and data standards. IT oversees and validates data, keeping information current, consistent and reliable.

Choose a solution that grows with you.

The flexible, extensible solution is available in both desktop and server environments so you can start small and grow as your needs change.

Free IT to focus on strategic business activities.

With a centralized platform and uniform standards, IT is freed from repetitive maintenance tasks. You can save and reuse data integration and data quality jobs and workflows, and both business and IT can use the point-and-click interface to visually explore data for quality issues and create workflows.

Screenshots

Features

  • Data profiling
  • Data monitoring
  • Data quality
  • Entity resolution

  • Data exploration
  • Data integration
  • Master data management foundation 

Technical Information

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