Data quality evaluation system
AssigneeCollectiveHealth, Inc.
InventorsKasey Eunice, Roman Kisin
Life of this patent
Estimating the term…
Abstract
A data quality evaluation system can automatically detect one or more types of data anomalies or other data quality issues associated with a data processing system that may impact the quality of output generated by the data processing system. For example, the data quality evaluation system can detect data errors associated with data, detect when data is not received by the data processing system in compliance with defined schedules, detect when elements of the data processing system may be mishandling data, and/or detect when patterns of data does not correspond with historical patterns or validation data. By automatically detecting such data quality issues, technical issues or problems causing the data quality issues can be investigated and corrected.
Claims21
A computer-implemented method, comprising:
- detecting, by one or more processors, and using a data quality evaluation system, a data quality issue associated with data received or processed by a data processing system that is configured to generate output based on the data, wherein:
- the data quality issue impacts quality of the output generated by the data processing system,
- the data quality issue indicates that an amount of the data received or processed by the data processing system differs from an expected amount by more than a threshold degree, and
- the data quality evaluation system comprises at least one of:
- a processing stage anomaly detector configured to detect the data quality issue in association with individual processing stages of the data processing system,
- a pattern anomaly detector configured to detect the data quality issue based on historical patterns, or
- a data quality validator configured to detect the data quality issue based on validation data corresponding to the data;
- generating, by the one or more processors, and using the data quality evaluation system, data quality results associated with the data quality issue;
- and
- generating, by the one or more processors, and using the data quality evaluation system based at least in part on the data quality results, at least one of a data quality scorecard or an anomaly notification.
(canceled)
One or more computing devices, comprising:
- one or more processors;
- and
- memory storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
- detecting, using a data quality evaluation system, a data quality issue associated with data received or processed by a data processing system that is configured to generate output based on the data, wherein:
- the data quality issue impacts quality of the output generated by the data processing system,
- the data quality issue indicates that an amount of the data received or processed by the data processing system differs from an expected amount by more than a threshold degree, and
- the data quality evaluation system comprises at least one of:
- a processing stage anomaly detector configured to detect the data quality issue in association with individual processing stages of the data processing system,
- a pattern anomaly detector configured to detect the data quality issue based on historical patterns, or
- a data quality validator configured to detect the data quality issue based on validation data corresponding to the data;
- generating, using the data quality evaluation system, data quality results associated with the data quality issue;
- and
- generating, using the data quality evaluation system based at least in part on the data quality results, at least one of a data quality scorecard or an anomaly notification.
One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
- detecting, using a data quality evaluation system, a data quality issue associated with data received or processed by a data processing system that is configured to generate output based on the data, wherein:
- the data quality issue impacts quality of the output generated by the data processing system,
- the data quality issue indicates that an amount of the data received or processed by the data processing system differs from an expected amount by more than a threshold degree, and
- the data quality evaluation system comprises at least one of:
- a processing stage anomaly detector configured to detect the data quality issue in association with individual processing stages of the data processing system,
- a pattern anomaly detector configured to detect the data quality issue based on historical patterns, or
- a data quality validator configured to detect the data quality issue based on validation data corresponding to the data;
- generating, using the data quality evaluation system, data quality results associated with the data quality issue;
- and
- generating, using the data quality evaluation system based at least in part on the data quality results, at least one of a data quality scorecard or an anomaly notification.
Dependencies are inferred from the claim text.