US 12,332,921 B1
Systems and methods for a graph database
Heather Marie Gavlak, Delaware, OH (US); Richard Gregory Barker, Gibsonia, PA (US); Evan Michael Sorger, Berea, OH (US); and Kevin William Black, Pittsburgh, PA (US)
Assigned to THE PNC FINANCIAL SERVICES GROUP, INC., Pittsburgh, PA (US)
Filed by The PNC Financial Services Group, Inc, Pittsburgh, PA (US)
Filed on Oct. 19, 2023, as Appl. No. 18/381,999.
Claims priority of provisional application 63/489,143, filed on Mar. 8, 2023.
Int. Cl. G06F 16/00 (2019.01); G06F 16/28 (2019.01); G06F 16/901 (2019.01); G06N 20/00 (2019.01)
CPC G06F 16/288 (2019.01) [G06F 16/285 (2019.01); G06F 16/9024 (2019.01); G06N 20/00 (2019.01)] 18 Claims
OG exemplary drawing
 
1. A computer-system for maintaining a relational data model for storage in a database, comprising:
a storage device that stores instructions; and
at least one processor that executes the instructions to:
generate, using a machine learning model, a data analysis algorithm trained to predict relationships in a data domain according to an architectural framework, wherein the architectural framework includes four levels: a business level, an application level, a data level and a technology level;
logically segregating, using the data analysis algorithm, each data domain based on the architectural framework, wherein the logical segregation includes organizing data within each data domain into one of the four levels of the architectural framework;
access a graph database that includes nodes and edges as a data model for representing data objects of the data domain according to the architectural framework, the nodes being configured to store first-class entities and the edges being configured to store relationships between the first-class entities;
store individual data objects of the data domain within the database according to relationships between the first-class entities in the data domain, the relationships containing architectural properties of the architectural framework, for an instance of querying, the querying including searching for applications within the data domain;
query the data objects using a modeling language for the database;
apply the data analysis algorithm to identify patterns in the graph database; and
draw the identified graph patterns on the graph database.