Metadata driven dataset management

Patent metadata

Field	Value
Publication number	US-11893024-B2
Application number	US-202318159582-A
Country	US
Kind code	B2
Filing date	Jan 25, 2023
Priority date	Nov 30, 2017
Publication date	Feb 6, 2024
Grant date	Feb 6, 2024

Abstract

A method for configuring the operation of the software of a data as a service (DAAS) system during run time is described. The configuring includes at least one of configuring ingestion of a vendor dataset to produce an ingested dataset and which analysis operations to perform on the vendor dataset to produce an analyzed dataset, and the configuring also includes at least one of how to search the vendor dataset based on a search query from a customer to allow the customer to locate a new record from the vendor dataset and how to match records in the vendor dataset with a match query from the customer to provide an updated record to the customer.

First claim

What is claimed is:

1. A method for configuring operation of software of a data as a service (DAAS) system, wherein the configuring is in relation to analysis of a vendor dataset and indicates how to match records in the vendor dataset with a match query from a customer to provide an updated record to the customer, the method comprising:
providing, by the DAAS system, a plurality of connections to a set of one or more vendor datasets representing data of vendors to be made accessible to a customer of the DAAS system;
receiving, by the DAAS system, metadata configuring one or more of the plurality of connections, wherein the metadata configures a respective vendor dataset to map to data fields of the DAAS system;
analyzing, by the DAAS system, data of the one or more of the vendor datasets to produce an analyzed dataset based on the one or more connections;
querying, by the DAAS system, the analyzed dataset to produce a match query result, wherein the querying includes a match key based on the metadata; and
providing, by the DAAS system, a query result to enrich a customer record, wherein the query result is determined by one or more of a match rule and a match ranking of the metadata.

2. The method of claim 1 , wherein the metadata configures mappings of respective fields of the customer record to be enriched by different vendor datasets.

3. The method of claim 1 , wherein the metadata comprises search metadata that indicates a set of analysis operations to be performed on the data of the one or more vendor datasets.

4. The method of claim 3 , wherein the set of analysis operations are indicated in the search metadata through one or more analysis types, wherein each analysis type in the one more analysis types identifies an ordered set of one or more analysis operations from the set of analysis operations.

5. The method of claim 4 , wherein the one or more analysis types are defined in a data analysis dictionary, wherein the data analysis dictionary is a state machine in which each analysis operation in the set of analysis operations is represented by a state in the state machine and the ordered group of analysis operations for each analysis type is defined by a pathway through states in the state machine.

6. The method of claim 3 , wherein the set of analysis operations include one or more of a normalization operation, a tokenization operation, a character filtering operation, a token filtering operation, a data field generation operation, an indexing operation, and a storing operation.

7. The method of claim 3 , wherein the search metadata and one or more of the match key, the match rule, and the match ranking are received at run time of the DAAS system.

8. A data as a service (DAAS) system that configures operation of software of the DAAS system, wherein the configuring is in relation to analysis of a vendor dataset and indicates how to match records in the vendor dataset with a match query from a customer to provide an updated record to a customer of the DAAS system, the DAAS system comprising:
a processor coupled to a non-transitory machine-readable storage medium, the non-transitory machine-readable storage medium storing:
an analysis service to analyze data of a set of one or more vendor datasets, which represents data of vendors to be made accessible to the customer, to produce an analyzed dataset, wherein metadata configures one or more of a plurality of connections of the DAAS system to the set of one or more vendor datasets, wherein the metadata configures a respective vendor dataset to map to data fields of the DAAS system;
a match service to:
query the analyzed dataset to produce a match query result, wherein the querying includes a match key based on the metadata; and
determine a query result to enrich a customer record, wherein the query result is determined by one or more of a match rule and a match ranking of the metadata; and

a serving interface to provide the match query result and the query result to the customer.

9. The DAAS system of claim 8 , wherein the metadata configures mappings of respective fields of the customer record to be enriched by different vendor datasets.

10. The DAAS system of claim 8 , wherein the metadata comprises search metadata that indicates a set of analysis operations to be performed on the data of the one or more vendor datasets.

11. The DAAS system of claim 10 , wherein the set of analysis operations are indicated in the search metadata through one or more analysis types, wherein each analysis type in the one more analysis types identifies an ordered set of one or more analysis operations from the set of analysis operations.

12. The DAAS system of claim 11 , wherein the one or more analysis types are defined in a data analysis dictionary, wherein the data analysis dictionary is a state machine in which each analysis operation in the set of analysis operations is represented by a state in the state machine and the ordered group of analysis operations for each analysis type is defined by a pathway through states in the state machine.

13. The DAAS system of claim 10 , wherein the set of analysis operations include one or more of a normalization operation, a tokenization operation, a character filtering operation, a token filtering operation, a data field generation operation, an indexing operation, and a storing operation.

14. The DAAS system of claim 10 , wherein the search metadata and one or more of the match key, the match rule, and the match ranking are received at run time of the DAAS system.

15. A non-transitory computer-readable storage medium storing instructions which, when executed by a set of one or more processors of an electronic device, cause the electronic device to:
provide a plurality of connections to a set of one or more vendor datasets representing data of vendors to be made accessible to a customer of the electronic device;
receive metadata configuring one or more of the plurality of connections, wherein the metadata configures a respective vendor dataset to map to data fields of the electronic device;
analyze data of the one or more of the vendor datasets to produce an analyzed dataset based on the one or more connections;
query the analyzed dataset to produce a match query result, wherein the querying includes a match key based on the metadata; and
provide a query result to enrich a customer record, wherein the query result is determined by one or more of a match rule and a match ranking of the metadata.

16. The non-transitory computer-readable storage medium of claim 15 , wherein the metadata configures mappings of respective fields of the customer record to be enriched by different vendor datasets.

17. The non-transitory computer-readable storage medium of claim 15 , wherein the metadata comprises search metadata that indicates a set of analysis operations to be performed on the data of the one or more vendor datasets.

18. The non-transitory computer-readable storage medium of claim 17 , wherein the set of analysis operations are indicated in the search metadata through one or more analysis types, wherein each analysis type in the one more analysis types identifies an ordered set of one or more analysis operations from the set of analysis operations.

19. The non-transitory computer-readable storage medium of claim 18 , wherein the one or more analysis types are defined in a data analysis dictionary, wherein the data analysis dictionary is a state machine in which each analysis operation in the set of analysis operations is represented by a state in the state

Assignees

• Salesforce Inc

Inventors

• Bansal Kaushal
• Tejomurtula Venkata Muralidhar
• Feroz Azeem
• Kashyn Dmytro
• Kudriavtsev Dmytro
• Shi Shouzhong
• Jain Ajitesh

Classifications

• G06F16/81 Primary

  Indexing, e.g. XML tags; Data structures therefor; Storage structures · CPC title

• G06F16/2455 Primary

  Query execution · CPC title

• G06F16/2228

  Indexing structures · CPC title

• G06F16/24578

  using ranking · CPC title

• G06F16/252

  between a Database Management System and a front-end application · CPC title