James Taylor First Look - SAS Enterprise Miner 7.1

I got an update on Enterprise Miner™ from the folks at SAS recently. Enterprise Miner is their development tool for data miners and predictive analytic specialists and is a graphical environment for designing and executing the steps in the creation of a predictive analytic model. Enterprise Miner 7.1 was part of the SAS 9.3 release that was released July 12^th 2011.

Key elements in the a new release were improved incorporation of the timing element (survival and time series data mining), insurance pricing models for rate making (a challenge due to the large number of people who make no claims relative to the those who make really large claims), credit scorecard extensions and full spectrum SAS data mining in Teradata 13.

Managing the time dimension of data is important in data mining as changes over time are some of the most predictive elements of your data. As a result time series data mining has always been part of how folks do data mining. SAS has added tools for reducing the dimensionality of data to enable similarity analysis (finding transactions that are like ones known to be fraudulent for instance) and matching patterns that include multiple transactions over time. Automated data preparation steps have been added to make it easier to include temporal relationships in modeling (automatically creating average daily balances by time period for instance).

Survival analysis has been added to allow the prediction of event probabilities at discrete time intervals along with competing risks - the overall survival function is overlaid with a hazard function to break down the risk by discrete time periods. For instance an overall churn survival rate over 24 months might be broken down into discrete intervals to show much higher risk of churn in the first month and the last. This function also allows you to calculate "mean residual life" for customers - an essential ingredient for customer life time value calculations (after all if you don't know how long you are likely to keep a customer you can hardly calculate their value to you).

... Other enhancements to the product include support for Support Vector Machines, increased PMML 4.0 support in scoring code (including some support for specifying the transformations a model needs using the new transformation schema), improvements in decision tree interactive pruning and improvements in the SAS Rapid Predictive Modeler interface.

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