System and method for data quality monitors

1. A computer-implemented method, performed by a computing system having one or more hardware computer processors and one or more non-transitory computer readable storage device storing software instructions executable by the computing system to perform the computerized method comprising:

receiving a plurality of data records from multiple data sources, wherein each of the data records includes a plurality of property values associated with a corresponding plurality of property types, and wherein data records from different data sources include different property types;

for each of a plurality of person data objects:

identifying a subset of the plurality of data records that are likely associated with a person indicated in the person data object; and

updating the person data object to include property values of the identified subset of data records;

identifying person data objects with potential data quality problems by:

receiving user selection of a data quality problem;

receiving user selection of one or more properties of person data objects; and

analyzing property values of the selected one or more properties for the selected data quality problem;

generating a user interface indicating the person data objects identified as having potential data quality problems, and including one or more properties of the person data objects having potential data quality problems;

receiving an indication of how to resolve the potential data quality problems; and

implementing the indicated resolution.

2. The computer-implemented method of claim 1 , wherein the data quality problem comprises at least one of: possible duplicate objects, missing properties, multi-valued properties, unparsed properties, disallowed enumerations, numeric range violations, or date range violations.

3. The computer-implemented method of claim 1 , wherein said implementing the indicated resolution comprises:

removing one or more property values of the person data object.

4. The computer-implemented method of claim 1 , wherein the data quality problem is possible duplicate objects, and identifying person data objects with potential data quality problems comprises identifying respective person data objects each having common property values for a predetermined quantity of the selected one or more properties.

5. The computer-implemented method of claim 1 , wherein the indication of how to resolve the potential data quality problem comprises an indication of two or more objects having potential data quality problems that are duplicates; and

said implementing the indicated resolution comprises combining the two or more indicated objects into a single object.

6. The computer-implemented method of claim 4 , wherein the one or more properties of person data objects received from the user indicates a quantity of the identified respective person data objects sharing the selected one or more properties.

7. The computer-implemented method of claim 1 , wherein the data quality problem is missing properties; and said identifying person data objects with potential data quality problems comprises identifying respective person data objects that are missing a predetermined of the selected one or more properties.

8. The computer-implemented method of claim 1 , wherein the data quality problem is multi-valued properties; and said identifying person data objects with potential data quality problems comprises identifying respective person data objects that have multiple values for ones of the selected one or more properties.

9. The computer-implemented method of claim 8 , wherein the indication of how to resolve the potential data quality problem comprises an indication of one of the multiple values that is correct; and

said implementing the indicated resolution further comprises removing all of the multiple values except for the indicated one or multiple values that is correct.

10. The computer-implemented method of claim 1 , wherein the data quality problem is numeric range violation; and said identifying person data objects with potential data quality problems comprises identifying respective person data objects that have property values that violate an allowed numeric range for the respective selected property.

11. The computer-implemented method of claim 1 , further comprising receiving one or more Boolean operators for the selected one or more properties and/or an indication of how many of the selected one or more properties are required to identify respective person data objects as potentially having the data quality problem.

12. A computing system comprising a hardware computer processor and a non-transitory computer readable medium having software instructions stored thereon, the software instructions executable by the hardware computer processor to cause the computing system to perform operations comprising:

receiving a plurality of data records from multiple data sources, wherein each of the data records includes a plurality of property values associated with a corresponding plurality of property types, and wherein data records from different data sources include different property types;

for each of a plurality of data objects of a first type:

identifying a subset of the plurality of data records that are likely associated with an object indicated in the person data object; and

updating the data object of the first type to include property values of the identified subset of data records;

identifying data objects of the first type with potential data quality problems by:

receiving user selection of a data quality problem;

receiving user selection of one or more properties of data objects of the first type; and

analyzing property values of the selected one or more properties for the selected data quality problem;

generating a user interface indicating the data objects of the first type identified as having potential data quality problems, and including one or more properties of the data objects of the first type having potential data quality problems;

receiving an indication of how to resolve the potential data quality problems; and

implementing the indicated resolution.

13. The computing system of claim 12 , wherein the data quality problem comprises at least one of: possible duplicate objects, missing properties, multi-valued properties, unparsed properties, disallowed enumerations, numeric range violations, or date range violations.

14. The computing system of claim 12 , wherein said implementing the indicated resolution comprises removing one or more property values of the data object of the first type.

15. The computing system of claim 12 , wherein the data quality problem is possible duplicate objects, and identifying data objects of the first type with potential data quality problems comprises identifying respective data objects of the first type each having common property values for a predetermined quantity of the selected one or more properties.

16. The computing system of claim 12 , wherein the indication of how to resolve the potential data quality problem comprises an indication of two or more objects having potential data quality problems that are duplicates; and said implementing the indicated resolution comprises combining the two or more indicated objects into a single object.

17. The computing system of claim 12 , wherein the data quality problem is missing properties; and said identifying data objects of the first type with potential data quality problems comprises identifying respective data objects of the first type that are missing a predetermined of the selected one or more properties.

18. The computing system of claim 12 , wherein the data quality problem is multi-valued properties; and said identifying data objects of the first type with potential data quality problems comprises identifying respective data objects of the first type that have multiple values for ones of the selected one or more properties.

19. The computing system of claim 18 , wherein the indication of how to resolve the potential data quality problem comprises an indication of one of the multiple values that is correct; and

said implementing the indicated resolution further comprises removing all of the multiple values except for the indicated one or multiple values that is correct.

20. The computing system of claim 12 , further comprising receiving one or more Boolean operators for the selected one or more properties and/or an indication of how many of the selected one or more properties are required to identify respective data objects of the first type as potentially having the data quality problem.