SAS Data Quality for Midsize Business helps you assess, improve, monitor and manage the quality of all your data, structured and unstructured.
As a result, you can rely on it to make strategic decisions and improve core operational processes. Designed and priced for small and midsize businesses, the easy-to-use solution is suited for both business and IT users. Highly flexible, the solution is available in desktop and client/server environments so you can start small and grow as your needs change.
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.
- Data profiling
- Data monitoring
- Data quality
- Entity resolution
- Data exploration
- Data integration
- Master data management foundation