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STATISTICALLY AND ONTOLOGICALLY CORRELATED ANALYTICS FOR BUSINESS INTELLIGENCE

  • US 20160232464A1
  • Filed: 03/28/2016
  • Published: 08/11/2016
  • Est. Priority Date: 02/11/2015
  • Status: Active Application
First Claim
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1. A method for business intelligence (BI) analytics, the method comprising:

  • performing, by one or more processing devices, an ontological analysis on data items in a relevant data set defined for a BI analytics query to determine one or more correlations of the data items in the relevant data set with ontological concepts in an ontological concept subsystem;

    performing, by the one or more processing devices, a first statistical analysis on a set of direct analytics output data items from the relevant data set that are included in a direct BI analytics output to rank the direct analytics output data items in an order of influence on the direct BI analytics output;

    performing, by the one or more processing devices, a second statistical analysis on the data items in the relevant data set relative to the direct analytics output data items to determine one or more of the data items in the relevant data set that influence the respective direct analytics output data items, thereby generating a list of key drivers from among the data items in the relevant data set such that the list of key drivers has a ranking in an order of the influence;

    revising, by the one or more processing devices, the ranking of the list of key drivers based at least in part on the correlations of the key drivers with the ontological concepts; and

    generating, by the one or more processing devices, a correlated analytics output comprising information on one or more of the key drivers based on the ranking of the list of key drivers.

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