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Systems and methods for interest-driven business intelligence systems including geo-spatial data

  • US 10,140,346 B2
  • Filed: 06/24/2014
  • Issued: 11/27/2018
  • Est. Priority Date: 09/19/2013
  • Status: Active Grant
First Claim
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1. An interest-driven business intelligence system, comprising:

  • raw data storage configured to contain raw data and perform extract, transform, and load (ETL) processes;

    a data mart configured to;

    contain metadata that describes the raw data; and

    contain aggregate data, wherein the aggregate data comprises structured data generated using ETL processes from the raw data; and

    an intermediate processing layer;

    wherein the intermediate processing layer is configured to automatically;

    generate metadata describing the raw data;

    derive reporting data requirements from at least one report specification based on the metadata; and

    compile an interest-driven data pipeline based upon the reporting data requirements, where compiling the interest-driven data pipeline comprises;

    generating ETL processing jobs to generate geo-spatial data and aggregate data from the raw data by;

    filtering the raw data based on the metadata describing the raw data;

    determining bounding data based on the metadata describing the raw data;

    bounding the filtered raw data based on the bounding data;

    generating geo-spatial data based on the bounded filtered raw data;

    storing the geo-spatial data in the data mart, wherein the geo-spatial data is stored as first parallel arrays of data with a first parallel array representing first values of a first particular field of data;

    applying transformations to the raw data based on the metadata describing the raw data;

    generating aggregate data based on the transformed data; and

    storing the aggregate data in the data mart, wherein the aggregate data is stored as second parallel arrays of data with a second parallel array representing second values of a second particular field of data;

    identifying ordering data based on a dimension across a plurality of pieces of the geo-spatial data;

    ordering, based on the ordering data, the plurality of pieces of the geo-spatial data to obtain ordered geo-spatial data;

    determining a fad based on the ordered geo-spatial data;

    generating reporting data including data satisfying the reporting data requirements based on the geo-spatial data; and

    storing the reporting data in the data mart for exploration by an interest-driven data visualization system.

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