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Data processing systems for data-transfer risk identification, cross-border visualization generation, and related methods

  • US 10,454,973 B2
  • Filed: 10/12/2018
  • Issued: 10/22/2019
  • Est. Priority Date: 06/10/2016
  • Status: Active Grant
First Claim
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1. A computer-implemented data processing method for generating a visualization of one or more data transfers between one or more data assets, the method comprising:

  • identifying one or more data assets associated with a particular entity;

    analyzing the one or more data assets to identify one or more data elements stored in the identified one or more data assets;

    defining a plurality of physical locations and identifying, for each of the identified one or more data assets, a respective particular physical location of the plurality of physical locations;

    analyzing the identified one or more data elements to determine one or more data transfers between the one or more data systems in different particular physical locations;

    determining one or more regulations that relate to the one or more data transfers;

    generating a visual representation of the one or more data transfers based at least in part on the one or more regulations; and

    using at least one data model to identify the one or more data elements stored in the one or more identified data assets, the data model comprising;

    a respective digital inventory for each of the one or more data assets, each respective digital inventory comprising one or more inventory attributes selected from the group consisting of;

    one or more processing activities associated with each respective data asset;

    transfer data associated with each respective data asset; and

    one or more pieces of personal data associated with each respective data asset; and

    a data map identifying one or more electronic associations between at least two of the one or more data assets, wherein the method further comprises;

    receiving an attribute value for a particular inventory attribute of the one or more inventory attributes;

    modifying the respective digital inventory into a modified digital inventory that includes the attribute value; and

    storing the modified digital inventory as part of the data model.

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