It wasn’t that long ago that companies looking to analyze data would hire a Ph.D. or otherwise experienced statistician to sit in a back room and write long lines of code with complex algorithms. That’s no longer the case, with IBM’s SPSS Modeler around to help business analysts to gain data-based insights.
SPSS Modeler is an extensive predictive analytics platform that allows business people who don’t necessarily have any statistics background to perform powerful analytic processes and integrate these processes with their decision management.
What IBM has done is simplify the user interface with an intuitive design. Nodes, which are graphic icons, perform tasks used for data preparation, modeling, exporting and importing.
SPSS allows the user to try out a variety of modeling approaches and compare the results. It can be extended beyond your typical numerical and categorical analysis to provide tools for text analytics to analyze social networks, for example.
In my LearnQuest classes, I show students what they need to know to get the most out of SPSS Modeler — a sense of the lifecycle and best practices of analytics, the ability to collect the right data, while cleaning any “noise” in order to reduce inaccuracies and anomalies. We examine a few models and talk about the uniqueness of each one and how we can leverage multiple models to enhance our predictive accuracy.
The Intro to Modeler class is focused on the process of data manipulation, but the more advanced courses examine specific techniques of analytics and their predictive applications.
Along the way I work with students to adapt the application to their individual needs, and by the end they come away empowered by sophisticated methods that traditionally required advanced degrees (with none of the student loans).
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A predictive analytics platform that brings predictive intelligence to decisions made by individuals, groups, systems and the enterprise.