DATA QUALITY MONITORS

• US 20150012509A1
• Filed: 12/02/2013
• Published: 01/08/2015
• Est. Priority Date: 07/05/2013
• Status: Active Grant

• Current Assignee: Palantir Technologies Incorporated
• Original Assignee: Palantir Technologies Incorporated
• Inventors: Kirn, Malina
• Granted Patent: US 9,348,851 B2
• Time in Patent Office: Days
• US Class Current: 707/700
• CPC Class Codes: A61B 17/0057 Implements for plugging an opening in the wall of a hollow or tubular organ, e.g. for sealing a vessel puncture or closing a cardiac septal defect sutures A61B17/04; closing rectum or urethra near body surface A61F2/0009
• CPC Class Codes: A61B 17/0401 Suture anchors, buttons or pledgets, i.e. means for attaching sutures to bone, cartilage or soft tissue; Instruments for applying or removing suture anchors A61B17/0642 takes precedence; fixation devices for tendons or ligaments A61F2/0811
• CPC Class Codes: A61B 2017/00004 (bio)absorbable, (bio)resorbable, resorptive for implantable prostheses A61F2210/0004
• CPC Class Codes: A61B 2017/00623 Introducing or retrieving devices therefor
• CPC Class Codes: A61B 2017/00659 located only on one side of the opening
• CPC Class Codes: A61B 2017/0409 Instruments for applying suture anchors for applying suture clamps, clips or locks A61B2017/0488
• CPC Class Codes: A61B 2017/0456 Surface features on the anchor, e.g. ribs increasing friction between the suture and the anchor
• CPC Class Codes: A61B 2017/0459 Multiple holes in the anchor through which the suture extends and locking the suture when tension is applied
• CPC Class Codes: G06F 11/0751 Error or fault detection not based on redundancy power supply failures G06F1/30; network fault management H04L41/06
• 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 16/2365 Ensuring data consistency and integrity
• CPC Class Codes: G06F 16/24556 Aggregation; Duplicate elimination
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 3/04847 Interaction techniques to control parameter settings, e.g. interaction with sliders or dials

Abstract

Systems and methods are presented for data quality monitoring. Data quality monitors may be created and configured to identify objects with specified data quality issues and/or property values. Objects identified by a data quality monitor can be presented to users for confirmation and resolution. Properties used by the data quality monitor to match objects may also be displayed to users.

Claims

1. A computer system comprising:

one or more computer processors; and

a tangible storage device storing instructions configured for execution by the one or more computer processors in order to cause the computer system to;

receive, from a user of the computer system, a selection of a first object type;

receive, from the user of the computer system, a selection of one or more second object types that the first object type is required to be associated with;

identify respective objects of the first object type that are each associated with one or more of the second object types;

receive, from the user of the computer system, a selection of one or more data quality criterion to be identified in the identified objects;

determine one or more of the identified objects having properties matching one or more of the data quality criterion; and

generate a user interface indicating the determined one or more objects matching one or more of the data quality criterion.

2. The computer system of claim 1, wherein the data quality criterion are configured to identify potential data quality problems including at least one of:

possible duplicate objects, missing properties, multi-valued properties, unparsed properties, disallowed enumerations, numeric range violations, and date range violations.

3. The computer system of claim 2, wherein the potential data quality problem is missing properties;

and

said data quality criterion identify objects that are missing at least a property value that is predetermined to be necessary.

4. The computer system of claim 2, wherein the potential data quality problem is multi-valued properties, and

said data quality criterion identify objects having multiple property values for individual properties that are each predetermined to have only one property value.

5. The computer system of claim 1, wherein the second one or more object types comprise object types with one or more properties and/or property values used for identifying fraudulent transactions and/or object types used for crime investigations.

6. The computer system of claim 2, wherein the potential data quality problem is unparsed properties, and

said data quality criterion identify objects that have one or more property values including unparsed data.

7. The computer system of claim 6, wherein the unparsed data takes on a meaning unintended by a data source providing the unparsed data.

8. The computer system of claim 2, wherein the potential data quality problem is possible duplicate objects, and

said data quality criterion identify two or more objects each having common property values for a predetermined quantity of properties.

9. The computer system of claim 2, wherein the potential data quality problem is disallowed enumerations, and

said data quality criterion identify objects that have one or more property values including disallowed enumerations.

10. The computer system of claim 2, wherein the potential data quality problem is numeric range violation, and

said data quality criterion identify respective objects that have one or more property values that violate an allowed numeric range for the respective property.

11. The computer system of claim 2, wherein the potential data quality problem is date range violation, and

said data quality criterion identify objects that have one or more property values that violate an allowed date range for the respective properties.

12. A non-transitory computer-readable storage medium comprising computer-executable instructions that direct a computing system to:

receive, from a user of the computing system, a selection of a first object type;

receive, from the user of the computing system, a selection of one or more second object types that the first object type is required to be associated with;

identify respective objects of the first object type that are each associated with one or more of the second object types;

receive, from the user of the computing system, a selection of one or more data quality criterion to be identified in the identified objects;

determine one or more of the identified objects having properties matching one or more of the data quality criterion; and

generate a user interface indicating the determined one or more objects matching one or more of the data quality criterion.

13. The non-transitory computer-readable storage medium of claim 12, wherein the data quality criterion are configured to identify potential data quality problems including at least one of:

possible duplicate objects, missing properties, multi-valued properties, unparsed properties, disallowed enumerations, numeric range violations, and date range violations.

14. The non-transitory computer-readable storage medium of claim 13, wherein the potential data quality problem is missing properties;

and

said data quality criterion identify objects that are missing at least a property value that is predetermined to be necessary.

15. The non-transitory computer-readable storage medium of claim 13, wherein the potential data quality problem is multi-valued properties, and

said data quality criterion identify objects having multiple property values for individual properties that are each predetermined to have only one property value.

16. The non-transitory computer-readable storage medium of claim 13, wherein the potential data quality problem is unparsed properties, and

said data quality criterion identify objects that have one or more property values including unparsed data.

17. The non-transitory computer-readable storage medium of claim 16, wherein the unparsed data takes on a meaning unintended by a data source providing the unparsed data.

18. The non-transitory computer-readable storage medium of claim 13, wherein the potential data quality problem is possible duplicate objects, and

said data quality criterion identify two or more objects each having common property values for a predetermined quantity of properties.

19. The non-transitory computer-readable storage medium of claim 13, wherein the potential data quality problem is disallowed enumerations, and

said data quality criterion identify objects that have one or more property values including disallowed enumerations.

20. The non-transitory computer-readable storage medium of claim 13, wherein the potential data quality problem is numeric range violation, and

said data quality criterion identify respective objects that have one or more property values that violate an allowed numeric range for the respective property.