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Python and SPSS: Extending the Analytic Landscape

In a recent client engagement, our team was asked to establish a method to identify and report on deviations of normal file activity. This blog will examine the use of Python as a middleware application that deconstructs SPSS Statistics output into data components that are loaded into an MS SQL database and are then viewed on a Cognos dashboard.

The solution begins with SPSS Statistics, more specifically, Control Charts. This technique (actually there are several options) is a good approach for assessing the variation in events and identifying the deviation between common and unusual patterns. The SPSS Statistics implementation of Control Charts is easy to use and robust. The only limitation is the reporting of findings; while complete, there is little flexibility in customizing the report output other than using the SPSS legacy script language and report writer.

The following graphic and table illustrate the two core components of the control chart report which includes an informative graph as well as related rule violations.

Michael Gonzales, Ph.D

Michael L. Gonzales, Ph.D., is an active practitioner in the IT space with over 30 years of industry experience serving in roles of chief architect and senior solutions strategist. He...

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