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

November 2, 2017 No Comments

SOURCE: SAS

Cary, NC (Nov. 2, 2017) – For the 12th year, SAS is named a leader in Gartner’s October 2017 Magic Quadrant for Data Quality Tools*. SAS was recognized based on its completeness of vision and ability to execute.

“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 state 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.”

According to Gartner, “Leaders demonstrate strength in depth across the full range of data quality functions, including core functions (parsing, standardization and cleansing), profiling, interactive visualization, matching, multidomain support and business-driven workflow. Leaders 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.”

SAS data quality products include SAS® Data Management, and SAS Data Quality.

- SAS Data Management is built on the SAS Platform with a solid data quality foundation that helps organizations improve, integrate and govern data. No matter where the data is stored – from legacy systems to Hadoop – SAS Data Management helps organizations access the data they need and create data management rules. The product gives organizations a standard, repeatable method for improving and integrating data – without additional cost.

- SAS Data Quality delivers trusted data by supporting traditional and emerging data sources – such as Hadoop, Impala, Amazon Redshift and more – throughout the entire data life cycle. By improving data where it lives, SAS provides faster and more secure data access. With data constantly flowing in and out, businesses rely on SAS to establish repeatable processes that build and maintain high-quality data.

The newest release to the SAS Platform at the end of 2017 builds on SAS’ expertise in data quality and introduces a new product, SAS Data Preparation. SAS Data Preparation simplifies and expedites data access and integration without requiring coding knowledge, bringing data quality and data preparation for analytics to even more parts of an organization.

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

Gartner Disclaimer

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.

*Gartner, Inc., Magic Quadrant for Data Quality Tools, 24 October 2017.

About SAS

SAS is the leader in analytics. Through innovative analytics, business intelligence and data management software and services, SAS helps customers at more than 83,000 sites make better decisions faster. Since 1976, SAS has been giving customers around the world THE POWER TO KNOW®. SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration. Other brand and product names are trademarks of their respective companies. Copyright © 2017 SAS Institute Inc. All rights reserved.

 

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