SAS Brings Business Users Do-It-Yourself Predictive Analytics 
SAS has launched a Rapid Predictive Modeler aimed at letting business users develop predictive models for various scenarios, including customer segmentation, up-selling, cross-selling and campaign management.
SAS has launched a Rapid Predictive Modeler aimed at letting business users develop predictive models for scenarios across various industries. Examples include customer segmentation, up-selling, cross-selling and campaign management, customer acquisition and customer turnover, according to SAS officials.
SAS Rapid Predictive Modeler will let business users can generate models in a few simple steps. Specifically, business users will select data and other inputs they need to do their analysis, choose the types of outcomes and/or reports they want to see, and the SAS software will automatically process the data and select the best predictive models.
SAS Rapid Predictive Modeler models can also be deployed in-database, which allows results to be used to make faster decisions. In specific, SAS’ latest offering provides key analytics benefits to corporations and individual business end users, including:
- Lets business analysts and subject-matter experts analyze their data using familiar UIs of SAS Enterprise Guide or Microsoft Excel.
- Provides a range of basic, intermediate and advanced prebuilt models that use a broad range of classical and modern data modeling techniques.
- Automatically treats data to handle outliers, missing values, rare target events, skewed data, correlated variables, variable selection and model selection.
- Lets users develop modeling and scoring tables using the data preparation tasks to stack, transpose, join, filter and sample data.
ames Taylor, an analytics consultant and CEO of Decision Management Solutions said this of SAS’ offering in his ‘First Look’ post on his blog:
One key thing is that SAS RPM creates a modeler-friendly process flow and specification under the covers. This is good because business analysts are already building models today without exposing them to the modeling team. Models created using SAS RPM tasks, however, are visible to the analytic team and extensible, allowing analytic teams to collaborate with and empower business analysts. Analysts can create large number of models quickly without these becoming black boxes. Quantitative modelers can edit/extend the models for improvement over time – improving both collaboration and productivity.
SAS Rapid Predictive Modeler score code is also fully compatible with the SAS Scoring Accelerators for Netezza, IBM DB2, and Teradata
Mike Rote, Teradata Corp.’s Director of the SAS and Teradata Center of Excellence, said the SAS offering provided important functionality to customers. “Organizations are constantly looking for ways to speed up both the development and deployment of analytic applications. SAS Rapid Predictive Modeler provides key functionality in both areas,” Rote said in a statement.
SAS Rapid Predictive Modeler integrates with SAS Model Manager for central management, promotion and performance monitoring. It also integrates with SAS Scoring Accelerator, which allows the models to be deployed and then executed directly within the database environment to speed things up,
One early SAS customer endorsed the approach, especially for helping non-experts tap into the value of data analysis and data mining. “SAS Rapid Predictive Modeler ushers our ‘non’ data miners into the power of predictive analytics,” said Tim Rey, Manager of the Advanced Analytics group for The Dow Chemical Company, said in a statement. "Early in the process, users get to see if their target outcomes are likely to be explained by the input variables they chose—saving time by providing a quick reality check.”
