SAS scores highest in two of four use cases by industry research firm in advanced analytics platforms study
Evaluation helps enterprises select the right analytics to meet specific needs
SAS is the highest scorer in two of four use cases in Gartner’s recent Critical Capabilities for Advanced Analytics Platforms1 report. The analytics leader tied for first in a third use case and was second in the fourth.
Using a scale of one to five, with five being the highest possible score, SAS scored highest in:
- Traditional Data Exploration – 3.93
- Big Data Exploration – 4.01
- Traditional Data Production – 3.91 (tie)
SAS’ 3.97 in Gartner’s Big Data Production use case was the second-highest score for all 16 evaluated vendors.
Purpose-built SAS® Analytics
The SAS Analytics offerings considered by the Gartner report included: SAS Visual Statistics, SAS Visual Analytics, SAS Contextual Analysis, SAS University Edition, SAS In-Memory Statistics for Hadoop, SAS® Enterprise Miner™ and SAS Forecasting.
“SAS creates very targeted analytics products to answer application-specific needs,” said Malene Haxholdt, SAS Principal Product Marketing Manager. “Many of our customers are better served by analytics that precisely meet a requirement. In most cases ‘one size fits all’ doesn’t fit anyone very well.”
Haxholdt noted that in recent years advanced analytics use has spread beyond its traditional base of data scientists to line-of-business users and others less familiar with analytic modeling. They are now finding key insights through software with visual interfaces to data analytics.
The new Gartner advanced analytics capabilities report is a companion to its 2015 Magic Quadrant for Advanced Analytics Platforms report, published Feb. 19. The capabilities evaluation is intended to assist technology buyers in finding the most appropriate advanced analytics package, based on organizational need.
The Gartner report defines its advanced analytics use cases this way:
- Traditional data exploration. “The exploration of new business problems using traditional data sources.”
- Big data exploration. “The exploration of new business problems using big data sources.”
- Traditional data production. “The production of models for known business problems using traditional data sources.”
- Big data production. “The production of models for known business problems using big data sources.”
Gartner bases its advanced analytics platform use case scores on 10 critical capabilities: user experience; performance and scalability; platform and project management; delivery, integration and deployment; simulation; optimization; forecasting; predictive analytics; data exploration and visualization; and data access and manipulation.
Each capability is then weighted in terms of its relative importance for specific product or service use cases. Next, products/services are rated in terms of how well they achieve each of the critical capabilities. A score that summarizes how well they meet the critical capabilities for each use case is then calculated for each product/service.
To learn more about how Gartner views the advanced analytics market, please read “SAS a Leader in Gartner 2015 Magic Quadrant for Advanced Analytics Platforms.”
1 Gartner, Critical Capabilities for Advanced Analytics Platforms, Lisa Kart, Gareth Herschel, Alexander Linden, Feb. 24, 2015.
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.
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