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Driving Big Data Business Decisions Through Modeling and Scripting in JMP®

Veeraporn Kullatham veerapornkullat0​ , Life Cycle and Reliability Engineer, GE Power Services      

Brad Foulkes bradford.foulkes, Principal Engineer for Lifing Analytics, GE Power Services

To use data to drive business decisions, it often needs to be manipulated and analyzed, then put into a simple format that is easily digestible for the user. This presentation will be a case study of using JMP to translate a very messy data set into a format that my business is able to use to help customers make decisions about operations. The analysis combines physics of failure and empirical data to better understand what is driving the events and what is not, and then help predict future events and remaining time until the event. Several aspects of JMP were used along the way, including table summary and row functions, survival modeling, scripting with database connections, regression modeling and graphical features for communication of results. JMP was also used for data manipulation and aggregation, as it allowed for superior performance over other database and desktop solutions. The result is a model that was useful to the end user and a script that can be run to easily perform the analysis in the future.

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