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SAS is a Leader in the 2017 Gartner Magic Quadrant for Data Quality Tools

Proud to be recognized for 12 years*** based on a comprehensive data management portfolio. 

Magic Quadrant for Data Quality Tools

Data quality solutions from SAS help you remediate data problems and make better business decisions.

When you have accurate, up-to-date information driving your processes, you can operate more efficiently. But good data quality isn't easy to achieve, especially when data is constantly streaming into your business from multiple sources.    

"More and more businesses are relying on their data assets to make strategic business decisions and increase revenue, but that’s only effective if those decisions are based on quality data," said Todd Wright, Senior Product Marketing Manager for Data Management at SAS. "SAS’ data quality tools enable organizations to make data decisions they can trust. We support organizations through every stage of the data quality process, making it easy to profile and identify problems, preview data and set up repeatable processes to maintain a high level of data quality."

The report's authors note that "Leaders demonstrate strength in depth across the full range of data quality functions … and exhibit a clear understanding of dynamic trends in the data quality market. They explore and execute thought-leading and differentiating ideas; and they deliver product innovations based on the market's demands."

"Analytics and operational endeavors need high-quality data, fast, to be effective," Wright said. "SAS will continue to lead in this space and add features and functions to its data quality offerings to meet customer needs in this dynamic market."

The data quality tools market continues to innovate, fueled by desire for cost reductions, information governance and digital business.


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*This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from SAS. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

**Magic Quadrant for Data Quality Tools by Mei Yang Selvage, Saul Judah and Ankush Jain, 24 October 2017.

***DataFlux in 2006-2011.

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