Since SAP’s acquisition of KXEN, announced in September 2013, many SAP Predictive Analysis users have been eager to preview the features KXEN Infinite Insight that will eventually be incorporated into SAP Predictive Analysis. In this blog, we’ll step through the same analysis of building a Customer Lifetime Value model that was discussed in my previous Customer Lifetime Value case study blog.
Configuring the Analysis
Infinite Insight has a much sparser interface, with relatively few options available. Unlike SAP Predictive Analysis, there is no algorithm selection, apart from describing the type of model that the user wants to create (Classification/Regression, Clustering, Time Series, or Association Rules). These line up with the algorithms that are most predominant in the current Predictive Analysis tool. In this case, we will select “Create a Classification/Regression Model”.
We now browse to and select the dataset that the model will be built on.
Infinite Insight automatically detects the data types found in the file and adds its own key.
The algorithm set up screen allows the user to set the target (dependent) and explanatory (independent) variables. By default, Infinite Insight will attempt to use all variables as explanatory factors in the model, but the user can designate specific variables to exclude. Variables that have no relevance to the target (like keys) and variables that are dependent on or determined by the target variable should be excluded from the model.
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About Hillary Bliss
Hillary Bliss is the Analytics Practice Lead at Decision First Technologies, and specializes in data warehouse design, ETL development, statistical analysis, and predictive modeling. She works with clients and vendors to integrate business analysis and predictive modeling solutions into the organizational data warehouse and business intelligence environments based on their specific operational and strategic business needs. She has a master’s degree in statistics and a MBA from Georgia Tech.