US 12,086,162 B2
Aggregation and analysis of data based on computational models
David Herman, Easton, PA (US); Mert Karakilic, Coquitlam (CA); and Padmini Ranganathan, Sunnyvale, CA (US)
Assigned to SAP SE, Walldorf (DE)
Filed by SAP SE, Walldorf (DE)
Filed on Sep. 14, 2017, as Appl. No. 15/705,171.
Prior Publication US 2019/0079990 A1, Mar. 14, 2019
Int. Cl. G06F 16/28 (2019.01); G06Q 10/06 (2023.01); G06Q 10/0635 (2023.01)
CPC G06F 16/285 (2019.01) [G06F 16/288 (2019.01); G06Q 10/0635 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A non-transitory machine-readable medium storing a program executable by at least one processing unit of a device, the program comprising sets of instructions for:
in response to receiving a request from a client device for an overall score for an entity, retrieving a first set of data associated with the entity and a second set of data associated with the entity;
receiving a first set of configuration settings for a first computational model;
generating the first computation model configured with the first set of configuration settings;
receiving a second set of configuration settings for a second computational model;
generating the second computation model configured with the second set of configuration settings;
using the first computational model to generate a first score for a first category based on the first set of the data, wherein the first computational model is an entity computation model and the first set of data is related to a plurality of attributes of the entity, the entity computation model generates the first score by combining individual scores for particular attributes across the plurality of attributes, wherein at least one individual score for a particular attribute is calculated based on one or more of a weight associated with the particular attribute and a mitigation factor associated with the first category;
using the second computational model to generate a second score for a second category based on the second set of data, wherein the second computational model is an incident computation model and the second set of data is related to a plurality of incidents associated with the entity, the incident computation model generates the second score by combining individual scores for particular incidents across the plurality of incidents, wherein at least one individual score for a particular incident is calculated based on one or more of an impact factor and a mitigation factor associated with the second category;
determining the overall score for the entity based on the first score and the second score; and
providing the overall score to the client device.