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Supermarket Data aggregated by Customer and info from shops pivoted to new columns.
Pennacchioli, D., Coscia, M., Rinzivillo, S., Pedreschi, D. and Giannotti, F., Explaining the Product Range Effect in Purchase Data. In BigData, 2013.
Model that will predict the quality of risk of a loan application. This dataset was initially created by dr. Hans Hofmann at the Institut fur Statistik und Okonometrie Universitat Hamburg.
Data taken from Dan Misener's KickbackMachine
The Sales Jan 2009 file contains some “sanitized” sales transactions during the month of January. Below is a sample of a report built in just a couple of minutes using the Blank Canvas app. These 998 transactions are easily summarized and filtered by transaction date, payment type, country, city, and geography
The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. The classification goal is to predict if the client will subscribe a term deposit
Netflix's catalog titles created using their OData catalog API at http://developer.netflix.com/docs/oData_Catalog. Great to see that October is the month when everybody gets ready for the Holiday season.
BBVA Innova challenge Big Data https://www.centrodeinnovacionbbva.com
BBVA contest. Credit card transactions stats in Barcelona and Madrid between Nov-2012 and Apr-2013
Zipcodes: Give a zone identifier and a commercial category, it returns the top postal codes where the clients with the most payments, unique cards and total spent originate.
Predicted field "Incomes" is the total income in a location (Seller Zipcode) and month, grouped by Commercial Category and Buyer Zipcode.