Automated dynamic data quality assessment

Patent metadata

Field	Value
Publication number	US-11295215-B2
Application number	US-201916433762-A
Country	US
Kind code	B2
Filing date	Jun 6, 2019
Priority date	Nov 22, 2013
Publication date	Apr 5, 2022
Grant date	Apr 5, 2022

Abstract

In general, embodiments of the present invention provide systems, methods and computer readable media for automated dynamic data quality assessment. One aspect of the subject matter described in this specification includes the actions of receiving a data quality job including a new data sample; and, if the new data sample is determined to be added to a reservoir of data samples, sending a quality verification request to an oracle; receiving a new data sample quality estimate from the oracle; and adding the new data sample and estimate to the reservoir. A second aspect of the subject matter includes the actions of receiving, from a predictive model, a judgment associated with a new data sample; analyzing the new data sample based in part on the judgment to determine whether to send a new data sample quality verification request to an oracle; and, if a new data sample quality estimate is received from the oracle, determining whether to add the new data sample and the judgment to the reservoir.

First claim

What is claimed is:

1. An apparatus comprising at least one processor and at least one memory storing instructions that, with the at least one processor, cause the apparatus to:
determine whether to add a new data sample to a reservoir of data samples identified based at least in part on a particular data type associated with the new data sample; and
in an instance in which the new data sample is to be added to the reservoir of data samples,
send the new data sample to an oracle of a plurality of oracles, the oracle selected based in part on one or more of the particular data type or one or more attributes associated with the new data sample;
receive, from the oracle, a data quality estimate associated with the new data sample from the oracle; and
add the new data sample and the associated data quality estimate to the reservoir of data samples.

2. The apparatus of claim 1 , wherein configuration data received with the new data sample comprises an oracle identifier.

3. The apparatus of claim 2 , wherein the oracle identifier identifies a particular oracle to provide a data quality estimate for the new data sample.

4. The apparatus of claim 3 , wherein the particular oracle is associated with an attribute of the new data sample.

5. The apparatus of claim 1 , the at least one memory further storing instructions that, with the at least one processor, cause the apparatus to:
update reservoir summary statistics associated with the reservoir of data samples.

6. The apparatus of claim 5 , wherein updating the reservoir summary statistics comprises:
calculating an overall data quality estimate for the reservoir using data quality estimates respectively associated with each data sample of the reservoir of data samples; and
calculating a statistical variance for the reservoir of data samples.

7. The apparatus of claim 1 , wherein the oracle is a crowd, a flat file of previously received crowd data verification results, or a software system.

8. The apparatus of claim 1 , wherein the new data sample is collected from a data stream.

9. The apparatus of claim 8 , wherein the new data sample is a single data instance or a set of data instances collected from the data stream within a pre-defined time window.

10. The apparatus of claim 1 , wherein the new data sample has been pre-processed by a data cleaning process.

11. A computer-implemented method, comprising:
determining, by a processor, whether to add a new data sample to a reservoir of data samples identified based at least in part on a particular data type associated with the new data sample; and
in an instance in which the new data sample is to be added to the reservoir of data samples,
sending, by the processor, the new data sample to an oracle of a plurality of oracles, the oracle selected based in part on one or more of the particular data type or one or more attributes associated with the new data sample;
receiving, by the processor and from the oracle, a data quality estimate associated with the new data sample from the oracle; and
adding, by the processor, the new data sample and the associated data quality estimate to the reservoir of data samples.

12. The method of claim 11 , wherein configuration data received with the new data sample comprises an oracle identifier.

13. The method of claim 12 , wherein the oracle identifier identifies a particular oracle to provide a data quality estimate for the new data sample.

14. The method of claim 13 , wherein the particular oracle is associated with an attribute of the new data sample.

15. The method of claim 11 , further comprising:
updating, by the processor, reservoir summary statistics associated with the reservoir of data samples.

16. The method of claim 15 , wherein updating the reservoir summary statistics comprises:
calculating an overall data quality estimate for the reservoir using data quality estimates respectively associated with each data sample of the reservoir of data samples; and
calculating a statistical variance for the reservoir of data samples.

17. The method of claim 11 , wherein the oracle is a crowd, a flat file of previously received crowd data verification results, or a software system.

18. The method of claim 11 , wherein the new data sample is collected from a data stream.

19. The method of claim 18 , wherein the new data sample is a single data instance or a set of data instances collected from the data stream within a pre-defined time window.

20. The method of claim 11 , wherein the new data sample has been pre-processed by a data cleaning process.

21. A computer program product, stored on a non-transitory computer readable medium, comprising instructions that when executed on one or more computers cause the one or more computers to:
determine whether to add a new data sample to a reservoir of data samples identified based at least in part on a particular data type associated with the new data sample; and
in an instance in which the new data sample is to be added to the reservoir of data samples,
send the new data sample to an oracle of a plurality of oracles, the oracle selected based in part on one or more of the particular data type or one or more attributes associated with the new data sample;
receive, from the oracle, a data quality estimate associated with the new data sample from the oracle; and
add the new data sample and the associated data quality estimate to the reservoir of data samples.

Assignees

• Groupon Inc

Inventors

• Daly Mark Thomas
• Jeffery Shawn Ryan
• Deland Matthew
• Pendar Nick
• James Andrew
• Johnston David

Classifications

• G06N20/00

  Machine learning · CPC title

• G06F16/2358

  Change logging, detection, and notification (replication G06F16/27) · CPC title

• G06F16/2365

  Ensuring data consistency and integrity · CPC title

• G06N5/02 Primary

  Knowledge representation; Symbolic representation · CPC title

• G06F16/215

  Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors · CPC title