SAS a Leader in 2016 Gartner Magic Quadrant for Data Quality Tools

Gartner’s November 2016 Magic Quadrant for Data Quality Tools places SAS in its Leaders quadrant, based on completeness of vision and ability to execute. This is the 11th year that SAS has been named a Leader.*

“About 40 percent of business initiatives fail due to data quality issues,” said Matthew Magne, Global Product Marketing Manager for Data Management at SAS. “SAS^® Data Quality puts organizations well on the road to resolving them. In addition to providing superior data profiling, governance, monitoring and process orchestration, SAS supports business users from data stewards to business analysts.”

According to Gartner, “Leaders demonstrate strength in depth and breadth across a full range of data quality functions, including profiling, parsing, standardization, matching, validation and enrichment. They exhibit a clear understanding and strategy for the data quality market, use thought-leading and differentiating ideas, and deliver their product innovation to the market.”

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.

“SAS continues to add features and functionality to its data quality offerings to stay ahead of customer needs,” added Magne. “We want to ensure our customers have ready, self-service access to high-quality data and are ready to attack machine learning, IoT and other initiatives with confidence.”

The report noted the importance of data quality for organizations of many types and sizes:

“The data quality tools market remains vibrant, owing to greater adoption on the demand side and consequently growth in market revenue on the supply side. We continue to see high demand for data quality tools from many verticals and organization sizes, including midsize organizations (which traditionally tended not to buy them). This demand for data quality tools is driven both by organizations continuing to invest in digital business initiatives as well as organizations seeking to cut costs and optimize business operations. Therefore, we see data quality tools being applied in a wide range of scenarios, such as BI and analytics (analytical scenarios), MDM (operational scenarios), information governance programs, ongoing operations, data migrations, and interenterprise data sharing.”

Learn more about the importance of data quality.

About the Magic Quadrant
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*SAS was named a leader in previous Magic Quadrants for Data Quality Tools under its former subsidiary name SAS DataFlux.