# US 2020/0401565 A1 · Automatically rank and route data quality remediation tasks > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2020/0401565 A1 - Document ID: US20200401565A1 - Status: Published application - Kind: A1 - Application number: 16/446,855 - Filed: 2019-06-20 - Published: 2020-12-24 - Earliest claimed: 2019-06-20 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Yannick Saillet; Namit Kabra; Manish Anand Bhide - Web page: https://patentgrep.com/patent/US20200401565A1 ## CPC - G06F 16/215: Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors - G06F 16/24578: {using ranking} - G06N 20/00: Machine learning - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract In an approach for automatically ranking and routing data quality remediation tasks, a processor analyzes a data set ingested by a repository to produce a set of data quality problems. A processor computes a score for each data quality problem of the set of data quality problems. A processor identifies a route to send each data quality problem of the set of data quality problems. A processor exports each data quality problem according to the score and the route. ## Claims ### Claim 1 A computer-implemented method for automatically ranking and routing data quality remediation tasks, the computer-implemented method comprising: analyzing, by one or more processors, a data set ingested by a repository to produce a set of data quality problems; computing, by the one or more processors, a score for each data quality problem of the set of data quality problems; identifying, by the one or more processors, a route to send each data quality problem of the set of data quality problems; and exporting, by the one or more processors, each data quality problem according to the score and the route. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein analyzing the data set further comprises: analyzing, by the one or more processors, the data set for data characteristics; tagging, by the one or more processors, the data set with business terms; identifying, by the one or more processors, a set of data quality rules; and searching, by the one or more processors, for the set of data quality problems based on the data characteristics, the business terms, and the set of data quality rules. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein the score is used to rank the set of data quality problems. ### Claim 4 (depends on 1) The computer-implemented method of claim 1, wherein the score for each data quality problem of the set of data quality problems is a function of a relevance of each data quality problem and an expected cost of resolution of each data quality problem, and wherein the score is a weighted average of the relevance and the expected cost of resolution with pre-defined weights. ### Claim 5 (depends on 4) The computer-implemented method of claim 4, wherein the relevance of each data quality problem is based on a set of data lineage metadata for the data set, and wherein the set of data lineage metadata is inspected for a set of dependent assets that use the data set as a source. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, wherein the route is a steward's computing device. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein identifying the route comprises: applying, by the one or more processors, a trained machine-learning model to identify a steward's computing device to send each data quality problem to. ### Claim 8 A computer program product for automatically ranking and routing data quality remediation tasks, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising: program instructions to analyze a data set ingested by a repository to produce a set of data quality problems; program instructions to compute a score for each data quality problem of the set of data quality problems; program instructions to identify a route to send each data quality problem of the set of data quality problems; and program instructions to export each data quality problem according to the score and the route. ### Claim 9 (depends on 8) The computer program product of claim 8, wherein the program instructions to analyze the data set further comprise: program instructions to analyze the data set for data characteristics; program instructions to tag the data set with business terms; program instructions to identify a set of data quality rules; and program instructions to search for the set of data quality problems based on the data characteristics, the business terms, and the set of data quality rules. ### Claim 10 (depends on 8) The computer program product of claim 8, wherein the score is used to rank the set of data quality problems. ### Claim 11 (depends on 8) The computer program product of claim 8, wherein the score for each data quality problem of the set of data quality problems is a function of a relevance of each data quality problem and an expected cost of resolution of each data quality problem, and wherein the score is a weighted average of the relevance and the expected cost of resolution with pre-defined weights. ### Claim 12 (depends on 11) The computer program product of claim 11, wherein the relevance of each data quality problem is based on a set of data lineage metadata for the data set, and wherein the set of data lineage metadata is inspected for a set of dependent assets that use the data set as a source. ### Claim 13 (depends on 8) The computer program product of claim 8, wherein the route is a steward's computing device. ### Claim 14 (depends on 8) The computer program product of claim 8, wherein the program instructions to identify the route comprise: program instructions to apply a trained machine-learning model to identify a steward's computing device to send each data quality problem to. ### Claim 15 A computer system for automatically ranking and routing data quality remediation tasks, the computer system comprising: one or more computer processors; one or more computer readable storage media; program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to analyze a data set ingested by a repository to produce a set of data quality problems; program instructions to compute a score for each data quality problem of the set of data quality problems; program instructions to identify a route to send each data quality problem of the set of data quality problems; and program instructions to export each data quality problem according to the score and the route. ### Claim 16 (depends on 15) The computer system of claim 15, wherein the program instructions to analyze the data set further comprise: program instructions to analyze the data set for data characteristics; program instructions to tag the data set with business terms; program instructions to identify a set of data quality rules; and program instructions to search for the set of data quality problems based on the data characteristics, the business terms, and the set of data quality rules. ### Claim 17 (depends on 15) The computer system of claim 15, wherein the score is used to rank the set of data quality problems. ### Claim 18 (depends on 15) The computer system of claim 15, wherein the score for each data quality problem of the set of data quality problems is a function of a relevance of each data quality problem and an expected cost of resolution of each data quality problem, and wherein the score is a weighted average of the relevance and the expected cost of resolution with pre-defined weights. ### Claim 19 (depends on 18) The computer system of claim 18, wherein the relevance of each data quality problem is based on a set of data lineage metadata for the data set, and wherein the set of data lineage metadata is inspected for a set of dependent assets that use the data set as a source. ### Claim 20 (depends on 15) The computer system of claim 15, wherein the program instructions to identify the route comprise: program instructions to apply a trained machine-learning model to identify a steward's computing device to send each data quality problem to.