Schema relationship discovery

Patent metadata

Field	Value
Publication number	US-2025390473-A1
Application number	US-202418752753-A
Country	US
Kind code	A1
Filing date	Jun 24, 2024
Priority date	Jun 24, 2024
Publication date	Dec 25, 2025
Grant date	—

Abstract

Methods, systems, apparatuses, and computer program products are described. A system may obtain a set of metadata associated with multiple entities of a datastore, the multiple entities including at least two different data types. The system may augment, using a generative artificial intelligence (AI) model, the set of metadata resulting in a set of augmented metadata for the multiple entities of the datastore. The system may generate, using the set of augmented metadata, a set of entity objects for the multiple entities of the datastore and in accordance with a reference schema. The system may identify, using the generative AI model and the set of entity objects as inputs into the generative AI model, first relationships between two or more first entities of the multiple entities of the datastore. Based on the identified relationships and a reference schema relationship model, the system may generate a schema relationship model.

First claim

Please enter the following amendments to the claims:

1 . A method for generating a schema relationship model, comprising:
obtaining a set of metadata associated with a plurality of entities of a datastore, the plurality of entities comprising at least two different data types; augmenting, using a generative artificial intelligence (AI) model, the set of metadata resulting in a set of augmented metadata for the plurality of entities of the datastore; generating, using the set of augmented metadata, a first set of entity objects for the plurality of entities of the datastore and in accordance with a reference schema, wherein generating the first set of entity objects transforms the set of metadata associated with the plurality of entities to a common format associated with the reference schema; identifying, using the generative AI model and the first set of entity objects as inputs into the generative AI model, one or more first relationships between two or more first entities of the plurality of entities of the datastore, wherein a first entity of the two or more first entities has a first data type and a second entity of the two or more first entities has a second data type; and generating the schema relationship model based at least in part on the identified one or more first relationships and in accordance with a reference schema relationship model.

2 . The method of claim 1 , wherein augmenting metadata for an entity of the plurality of entities comprises:
generating, using the metadata associated with the entity, data of the entity, or both as input into the generative AI model, augmented metadata for the entity, wherein the set of augmented metadata comprises the augmented metadata for the entity.

3 . The method of claim 2 , wherein generating the augmented metadata for the entity comprises:
generating information for one or more field descriptors, field identifiers, table descriptions, entity descriptions, or a combination thereof.

4 . The method of claim 1 , wherein identifying the one or more first relationships comprises:
identifying the one or more first relationships based at least in part on one or more second relationships between two or more second entities of the plurality of entities of the datastore, wherein the one or more second relationships are identified prior to identifying the one or more first relationships.

5 . The method of claim 1 , further comprising:
periodically executing a job that is configured to update the schema relationship model.

6 . The method of claim 1 , wherein metadata of the set of metadata for an entity of the plurality of entities comprises a table description of the entity, one or more field identifiers of the entity, one or more column identifiers of the entity, or any combination thereof.

7 . The method of claim 1 , wherein:
the datastore comprises a hybrid datastore that comprises a plurality of different data types.

8 . The method of claim 1 , further comprising:
generating, using the set of augmented metadata and based at least in part on the schema relationship model, a second set of entity objects for the plurality of entities of the datastore in accordance with the reference schema; identifying, using the generative AI model and the second set of entity objects as inputs into the generative AI model, one or more second relationships between two or more second entities; and generating an updated schema relationship model based at least in part on the identified one or more second relationships and in accordance with the reference schema relationship model.

9 . The method of claim 1 , wherein generating the first set of entity objects comprises:
generating a respective JavaScript Object Notation (JSON) object for each entity of the plurality of entities using the reference schema that is an empty JSON structure.

10 . The method of claim 1 , wherein the generative AI model comprises a large language model (LLM).

11 . The method of claim 1 , wherein the plurality of entities comprising the at least two different data types comprises one or more structured query language (SQL) entities, one or more not only SQL (NoSQL) entities, one or more documents, one or more binary large objects (BLOBs), one or more files, or any combination thereof.

12 . An apparatus for generating a schema relationship model, comprising:
one or more memories storing processor-executable code; and one or more processors coupled with the one or more memories and individually or collectively operable to execute the code to cause the apparatus to:
obtain a set of metadata associated with a plurality of entities of a datastore, the plurality of entities comprising at least two different data types;
augment, using a generative artificial intelligence (AI) model, the set of metadata resulting in a set of augmented metadata for the plurality of entities of the datastore;
generate, using the set of augmented metadata, a first set of entity objects for the plurality of entities of the datastore and in accordance with a reference schema, wherein generation of the first set of entity objects transforms the set of metadata associated with the plurality of entities to a common format associated with the reference schema;
identify, using the generative AI model and the first set of entity objects as inputs into the generative AI model, one or more first relationships between two or more first entities of the plurality of entities of the datastore, wherein a first entity of the two or more first entities has a first data type and a second entity of the two or more first entities has a second data type; and
generate the schema relationship model based at least in part on the identified one or more first relationships and in accordance with a reference schema relationship model.

13 . The apparatus of claim 12 , wherein, to augment metadata for an entity of the plurality of entities, the one or more processors are individually or collectively operable to execute the code to cause the apparatus to:
generate, using the metadata associated with the entity, data of the entity, or both as input into the generative AI model, augmented metadata for the entity, wherein the set of augmented metadata comprises the augmented metadata for the entity.

14 . The apparatus of claim 13 , wherein, to generate the augmented metadata for the entity, the one or more processors are individually or collectively operable to execute the code to cause the apparatus to:
generate information for one or more field descriptors, field identifiers, table descriptions, entity descriptions, or a combination thereof.

15 . The apparatus of claim 12 , wherein, to identify the one or more first relationships, the one or more processors are individually or collectively operable to execute the code to cause the apparatus to:
identify the one or more first relationships based at least in part on one or more second relationships between two or more second entities of the plurality of entities of the datastore, wherein the one or more second relationships are identified prior to identifying the one or more first relationships.

16 . The apparatus of claim 12 , wherein the one or more processors are individually or collectively further operable to execute the code to cause the apparatus to:
periodically execute a job that is configured to update the schema relationship model.

17 . The apparatus of claim 12 , wherein metadata of the set of metadata for an entity of the plurality of entities comprises a table description of the entity, one or more fiel

Assignees

• Salesforce Inc

Inventors

• Sipani Sourav
• Singh Ajay

Classifications

• G06F16/288

  Entity relationship models · CPC title

• G06F16/258

  Data format conversion from or to a database · CPC title

• G06F16/212 Primary

  with details for data modelling support · CPC title