SAS Visual Statistics for Modernized Analytics

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SAS_Institute_logoMany organizations around the world that grasp the value of big data are looking to SAS® Visual Statistics to speed model building and transform accurate analytic insight into business success faster and more accurately than ever. The new software is from SAS, a leader in advanced analytics.

With SAS Visual Statistics multiple users can build and modify predictive models on large volumes of diverse data, using analytical methods that include regression and estimation, classification, and clustering. They can then present the analytical results visually, which speeds the ability to discover relationships between variables and determine which will positively affect outcomes.

SAS’ secret is pairing fast, in-memory processing for near-instantaneous model execution with the highly interactive, drag-and-drop interface popularized by SAS Visual Analytics, a data visualization package now licensed at more than 1,500 sites. The in-memory architecture of SAS Visual Statistics retains data, even big data, in system memory to avoid repetitive and inefficient data loading from disk storage.

A key to optimal analytics insight is the ability to iteratively run models, each with a slight change, to determine which provides the greatest accuracy. SAS Visual Statistics is designed to provide near-real-time results so that data scientist productivity is maximized,” said Vice President and Research Director Tony Cosentino of Ventana Research. “Ventana’s research showed that close to half of organizations present their business analytics visually. By basing the SAS Visual Statistics interface on the popular SAS Visual Analytics offering, SAS is rising to a market need by providing advanced analytics through an increasingly popular user paradigm.”

In seconds or less, multiple SAS Visual Statistics users can see the impact of changes to model settings, such as adding new variables or removing outliers. They can easily and concurrently create models by specific variables, groups or segments to predict multiple outcomes.

DirectPay, a Netherlands-based debt management company, believes that information technology and analytics are the backbone of its fast-growing business. Already an enthusiastic SAS user, DirectPay is an eager early adopter of SAS Visual Statistics.

As we move to modernize our analytics infrastructure, we consider SAS Visual Statistics to be very useful in terms of new insights,” Said Colin Nugteren, DirectPay’s Manager of Operations. “Its speed and usability makes it a great tool. We are certain that this new software will improve both model quality and model deployment time, since more variables can be tested in different combinations in a short amount of time. With millions of payments processed through our systems, we need a tool like SAS Visual Statistics that is capable of analyzing large data sets in a minimum amount of time. Faster insights improve profitability.”

SAS Visual Statistics is not limited to big data environments such as DirectPay’s. It is equally valuable for departmental deployments or midsize businesses, operating on several platforms, including database appliances from Pivotal and Teradata, Hadoop distributions from Cloudera and Hortonworks, or departmental servers.


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