US 12,182,090 B1Granted

Systems and methods for generating data transfers using programming language-agnostic data modeling platforms

AssigneeCitibank, N.A.

InventorsChuan Li, Jim B. Adams, Yan Liu, Peter Huang, Alicia Wang

Life of this patent

Estimating the term…

Loading patent…

Abstract

Systems and methods for a programming language-agnostic data modeling platform that is both less resource intensive and scalable. Additionally, the programming language-agnostic data modeling platform allows for advanced analytics to be run on descriptions of the known logical data models, to generate data offerings describing underlying data, and to easily format data for compatibility with artificial intelligence systems. The systems and methods use a supplemental data structure that comprises logical data modeling metadata, in which the logical data modeling metadata describes the logical data model in a common, standardized language. For example, the logical data modeling metadata may comprise a transformer lineage of the logical data model.

Claims19

Dependent claims

A system for generating data transfers using programming language-agnostic data modeling platforms, the system comprising:

one or more processors;
and
a non-transitory, computer-readable medium comprising instructions recorded thereon that, when executed by the one or more processors, cause operations comprising:
receiving a first request to populate a first local data repository with a first dataset from a first data source, wherein the first data source uses a first conceptual data model that indicates a first relationship between a first entity and a second entity, and wherein the first local data repository has a first physical data model;
determining that the first data source uses a first logical data model;
based on determining that the first data source uses the first logical data model, selecting the first logical data model from a plurality of logical data models, wherein the plurality of logical data models correspond to a first conceptual data model;
retrieving a first supplemental data structure for the first logical data model, wherein the first supplemental data structure comprises a first attribute expressed in a standardized language, and wherein the first attribute comprises a first transformer lineage of the first logical data model;
determining the first entity for the first attribute;
determining a first data requirement for the first attribute based on the first entity;
determining a first data type based on the first attribute;
searching attributes of a second entity for data types corresponding to the first data type;
determining that a second attribute of the attributes of the second entity comprises the first data type;
assigning the first data requirement to the second attribute based on determining that the second attribute of the attributes of the second entity comprises the first data type;
determining a first mapping of the first logical data model to the first physical data model by mapping the first attribute to the first physical data model, wherein the first mapping maps the first attribute to a table of the first physical data model;
and
populating the first local data repository with the first dataset based on the first mapping and the first data requirement.

13 more elements

A method for generating data transfers using programming language-agnostic data modeling platforms, the method comprising:

receiving a first request to populate a first local data repository with a first dataset from a first data source, wherein the first data source uses a first logical data model, and wherein the first local data repository has a first physical data model;
in response to the first request, retrieving a first supplemental data structure for the first logical data model, wherein the first supplemental data structure is expressed in a standardized language and comprises a first attribute, and wherein the first attribute comprises a first transformer lineage of the first logical data model;
determining a first entity for the first attribute;
determining a first data requirement for the first attribute based on the first entity;
determining a first data type based on the first attribute;
searching attributes of a second entity for data types corresponding to the first data type;
determining that a second attribute of the attributes of the second entity comprises the first data type;
assigning the first data requirement to the second attribute based on determining that the second attribute of the attributes of the second entity comprises the first data type;
determining a first mapping of the first logical data model to the first physical data model by mapping the first attribute to the first physical data model;
and
populating the first local data repository with the first dataset based on the first mapping and the first data requirement.

8 more elements

A non-transitory, computer-readable medium comprising instructions recorded thereon that, when executed by one or more processors, cause operations comprising:

receiving a first request to populate a first local data repository with a first dataset from a first data source, wherein the first data source uses a first logical data model, and wherein the first local data repository has a first physical data model;
in response to the first request, retrieving a first supplemental data structure for the first logical data model, wherein the first supplemental data structure is expressed in a standardized language and comprises a first attribute, and wherein the first attribute comprises a first transformer lineage of the first logical data model;
determining a first entity for the first attribute;
determining a first data requirement for the first attribute based on the first entity;
determining a first data type based on the first attribute;
searching attributes of a second entity for data types corresponding to the first data type;
determining that a second attribute of the attributes of the second entity comprises the first data type;
assigning the first data requirement to the second attribute based on determining that the second attribute of the attributes of the second entity comprises the first data type;
determining a first mapping of the first logical data model to the first physical data model by mapping the first attribute to the first physical data model;
and
populating the first local data repository with the first dataset based on the first mapping and the first data requirement.

8 more elements

Dependencies are inferred from the claim text.

Facts

Application: 18/513,391Filed 17 Nov 2023 · continuation
Priority: 22 Jun 2023
Published: US 2024/0427749 A126 Dec 2024
Granted: 31 Dec 2024
Term ends: Not estimatedThe source records don’t support an estimate.

Classification3 codes

G06F 16/212
Schema design and management: with details for data modelling support
G06F 16/22
Of structured data, e.g. relational data: indexing; Data structures therefor; Storage structures
G06F
Computing and data processing

Family

Application18/339,269Parent of this continuation · filed 22 Jun 2023
US 11,829,340 B1Parent of this continuation
US 2024/0427749 A1Published application
US 12,182,090 B1This patent

From the US filing history. Foreign family members aren’t listed.

Timeline

Citations

Open elsewhere

Building an agent or pulling many patents? Use the API or MCP server instead of scraping pages. Get an API key