Oh My Darling! SPSS Says Goodbye Clementine, Hello 'PASW'

New software packaging focuses on predictive analytics. Upgrades streamline, automate time-consuming data-prep tasks.

Doug Henschen, Executive Editor, Enterprise Apps

April 9, 2009

2 Min Read

"Predictive analytics" is one of the hottest buzzwords in business intelligence these days, so it should come as no surprise that analytic software vendor SPSS is rebranding its core portfolio as SPSS Predictive Analytics Software (PASW). Even if each and every module in the suite doesn't fit a narrow definition of predictive analytics, the vendor says the larger business context is invariably about capturing data, predicting outcomes and acting on that insight.

"If you're doing text mining in a call center to understand customer behavior, for example, you're ultimately going to attach a score to that [analytic] and use it to act in some way to improve that interaction," explains David Vergara, director of product marketing at SPSS. "That's really a predictive use of the software."

The core elements of the PASW Portfolio announced on Monday include PASW Modeler 13 (formerly Clementine) and PASW Text Analytics 13 (formerly Text Mining for Clementine). Over the next year, SPSS says it will roll other software into an integrated PASW portfolio, including PASW Statistics (formerly SPSS Statistics), PASW Data Collection (formerly Dimensions) and PASW Collaboration and Deployment Services (formerly Predictive Enterprise Services). The goal is to create a cohesive software experience in addition to a clearer and stronger branding approach.

"We're trying to show users who may not be analytics experts how all these different products map together and create a logical workflow under the umbrella of Predictive Analytics Software," Vergara explains.

The new release includes substantive upgrades as well as cosmetic branding changes. For example, the PASW Modeler 13 user interface has been streamlined to take users through the entire data-mining process, from data access to model deployment. Data preparation has also been streamlined and automated.

"Automated data preparation features let users prepare and condition data in a single step, fixing quality issues and imputing missing values as needed," Vergara says. "The software will also report on all the changes and recommend not using a particular data set if there is too much missing information."

Other upgrades to PASW Modeler 13 include an Auto Cluster feature that determines the best cluster algorithm for a particular data set. The feature graphically displays the results so users can easily inspect and compare clusters. Functionality from PASW Statistics can be used within Modeler 13 to support statistical analysis without having to switch between applications.

Upgrades to PASW Text Analytics 13 include new prebuilt categories and dictionaries geared to employee, product and customer satisfaction surveys.

"PASW" may not trip off the tongue or inspire folk songs, the way the Clementine of Gold Rush days did. But by putting the emphasis on prediction, SPSS is riding a wave of mainstream interest in seeing into the future of business.

About the Author(s)

Doug Henschen

Executive Editor, Enterprise Apps

Doug Henschen is Executive Editor of InformationWeek, where he covers the intersection of enterprise applications with information management, business intelligence, big data and analytics. He previously served as editor in chief of Intelligent Enterprise, editor in chief of Transform Magazine, and Executive Editor at DM News. He has covered IT and data-driven marketing for more than 15 years.

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