Monthly Archives: October 2017


RapidMiner Market Basket Sample

RapidMiner Market Basket One method to create a targeted cross selling model is to use historical customer information and apply the prediction to existing customers.  In this example, I will be using fictitious customer account data for a financial institution such as a bank or credit union to create a RapidMiner Market Basket predictive model.  The Marketing department wants to send out targeted mailing and phone call campaigns to customers most likely to need an auto loan.  The available data includes information on each unique account along with flags that indicate use (1 used, 0 not used).  Other fields count the number of inbound calls, late payments, or number of months as a customer. Sample Financial Data Fields Account ID                                       10. Holiday Club Indicator Account Origin Indicator            [...]

By |2017-10-09T07:01:42+00:00October 9th, 2017|RapidMiner|0 Comments

Power BI Leveraging Tabular Models

Power BI Direct Query Power BI can be used in one of two modes to access data.  The import option loads data from the source data to the Power BI model.  Queries are then processed directly against the data in the model.  Using the DirectQuery option, on the other hand, leaves at the source and Power BI queries the data as needed.  For smaller tables using DirectQuery can be a good option to leverage when you do not want to build a data refresh process into Power BI.  Source systems can potentially be queried on demand and provide users with the most up to date data as possible.  DirectQuery does have limitations that you need to be aware such as connecting to a single database only, time intelligence is not available, and there is a million row limit. For complete benefits and limitations of Power BI see - Power BI Tabular [...]

By |2017-10-02T07:05:09+00:00October 2nd, 2017|Power BI|0 Comments