Recommending data enrichments

• US 9,244,956 B2
• Filed: 06/14/2011
• Issued: 01/26/2016
• Est. Priority Date: 06/14/2011
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Bice, Anthony Nino, Sivaramakrishnan, Hariharan, Robinson, David Michael
• Primary Examiner(s): Trujillo, James
• Assistant Examiner(s): SHECHTMAN, CHERYL MARIA
• Application Number:
  US13/159,654
• Publication Number:
  US 20120323843A1
• Time in Patent Office: 1,687 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06F 16/215 Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/90335 Query processing
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

The present invention extends to methods, systems, and computer program products for recommending data sources. A request to provide recommendations of data enrichments for a database is received at a recommendation engine. The recommendation engine may perform static and dynamic analysis of data associated with the database and may further refine recommendations based on policies. The recommendation engine may then provide the recommendations, if any, of data enrichments to allow a software developer, for example, to indicate whether the data enrichments are to be used.

Claims

1. At a computer system, the computer system including a processor, a method for recommending data enrichments for a database, the method comprising the processor:

receiving a request to provide data enrichment recommendations for the database;

analyzing metadata for the database, the metadata defining the structure of the database;

recommending a first data enrichment for the database based on the analysis of the metadata, the first data enrichment to supplement the database;

suggesting a second data enrichment for the database based on a similarity between the first data enrichment and the second data enrichment, the second data enrichment to supplement the database; and

identifying a data source capable of providing the second data enrichment by;

comparing a characteristic of a first query and a second query that obtain enrichment data for the second data enrichment from two different enriching data sources;

selecting an appropriate query based on the comparison of the characteristic of the first query and the second query; and

determining an identifier for the enriching data source associated with the appropriate query.

2. The method of claim 1, further comprising identifying a data source capable of providing the first data enrichment by:

finding an identifier within the metadata; and

mapping the identifier to the data source using a data structure that associates the identifier with the first data enrichment.

3. The method of claim 2, wherein finding an identifier within the metadata comprises finding a column name within the metadata and wherein mapping the identifier to the first enriching data source comprises using a table that associates identifiers with data enrichments.

4. The method of claim 2, wherein finding an identifier within the metadata comprises finding a table name within the metadata and wherein mapping the identifier to the first enriching data source comprises using a table that associates identifiers with data enrichments.

5. The method of claim 2, wherein finding an identifier within the metadata comprises finding a stored procedure name within the metadata and wherein mapping the identifier to the first enriching data source comprises using a table that associates identifiers with data enrichments.

6. The method of claim 2, wherein finding an identifier within the metadata comprises finding a data type of a column of the database and wherein mapping the identifier to the first enriching data source comprises searching a table that associates data types with data enrichments.

7. The method of claim 1, wherein recommending the first data enrichment comprises sending a name of the first data enrichment as well as an input data type for the first data enrichment and an output data type for the first data enrichment, the name, the input data type, and the output data type for use in developing software to reference data enrichments through the database.

8. The method of claim 1,

wherein selecting an appropriate query based on the comparison comprises selecting the fastest query depending on which of the first query and the second query have the smallest latency.

9. The method of claim 1, further comprising displaying an indication of the first data enrichment at a graphical interface.

10. The method of claim 1, wherein comparing a characteristic of a first query and a second query that obtain enrichment data for the second data enrichment from two different enriching data sources comprises comparing query times of the first query and the second query;

and

wherein selecting an appropriate query based on the comparison of the characteristic of the first query and the second query comprises selecting the fastest query of the first query and the second query based on comparison of the query times.

11. The method of claim 10, wherein selecting the fastest query of the first query and the second query based on comparison of the query times comprises selecting the fastest query of the first query and the second query depending on which of the first query and the second query have the smallest latency in obtaining enrichment data for the second data enrichment.

12. A system, the system comprising:

a processor;

system memory;

a database storing data and metadata regarding the data, the metadata defining the structure of the database;

one or more computer storage devices having stored thereon computer-executable instructions representing a recommendation engine, the recommendation engine configured to;

receive a request to provide data enrichment recommendations for the database;

analyze the metadata;

recommend a first data enrichment for the database based on the analysis of the metadata, the first data enrichment to supplement the database;

suggest a second data enrichment for the database based on a similarity between the first data enrichment and the second data enrichment to supplement the database; and

identify a data source capable of providing the second data enrichment by;

selecting a fastest query from a first query and a second query that obtain enrichment data for the second data enrichment from different data sources based on query times of the first query and the second query; and

determining an identifier for the data source associated with the fastest query.

13. The system of claim 12, wherein the DBMS, the database, and the recommendation engine are hosted on one or more servers located remotely from the software component, and wherein the software component is used by a software developer to augment the database.

14. The system of claim 12, wherein the DBMS, the database, the recommendation engine, and the software component are hosted on a computer, and wherein the software component is an application.

15. The system of claim 12, wherein the recommendation engine being configured to recommend the first data enrichment comprises the recommendation engine being configured to:

find an identifier within the metadata; and

map the identifier to the first data enrichment using a data structure that associates the identifier with the first data enrichment.

16. The system of claim 12, wherein the recommendation engine being configured to select a fastest query from a first query and a second query comprises the recommendation engine being configured to select the fastest query depending on which of the first query and the second query have the smallest latency.

17. A computer storage medium having computer-executable instructions, which when executed perform actions, comprising:

receiving a request to provide data enrichment recommendations for the database;

analyzing metadata for the database, the metadata defining the structure of the database;

recommending a first data enrichment for the database based on the analysis of the metadata, the first data enrichment to supplement the database;

suggesting a second data enrichment for the database based on a similarity between the first data enrichment and the second data enrichment to supplement the database; and

identifying a data source capable of providing the second data enrichment by;

selecting a query with the fastest query time from among a first query and a second query that access the second enrichment data from different data sources; and

determining an identifier for data source associated with the query.

18. The computer storage medium of claim 17, further comprising receiving a data structure that associates recommendations with enriching data sources and displaying at least a portion of the recommendations and their associated enriching data sources via a graphical interface.

19. The computer storage medium of claim 17, further comprising providing one or more policies that are to be satisfied in conjunction with recommending the first data enrichment.

20. The computer storage medium of claim 17, wherein selecting a query with the fastest query time from among a first query and a second query comprises selecting a query with the smallest latency from among the first query and the second query.