User Tools

Site Tools


data_quality_management_system:data_quality_issue

Data quality issue

Definition

A data quality issue is an issue with regard to data quality.

Notes

Generally, a data quality issue concerns an incorrect data value, but it may also involve any other data quality dimensions, e.g., completeness and timeliness.

Attributes of a data quality issue are:

  • Description of a data quality issues
  • Classification of a data quality issues
  • Impact, severity/urgency
  • Assignment of the data quality issues to a person who will resolve the data quality issues
  • What is changed, why en how in the resolution of a data quality issues
  • Resolution time/Duration

Synonym(s)

  • Data anomalies
  • Data error
  • Data quality incident
  • Defect
  • Error
  • Nonconformity

Lifecycle

Phase Activity
Plan * To detect or identify data quality issues
* To determine if similar data quality issues exist
* To register data quality issues
* To count the number of data quality issues
* To categorize or classify data quality issues
* To diagnose data quality issues(‘root cause analysis’)
* To formulate options for remediation of data quality issues.
* To assess the business impact of data quality quality issues(‘severity’)
* To prioritize data quality issuesbased on business impact (by data owners and data stewards)
* To eventually escalate data quality issues. See figure.
Do * To eliminate or resolve a data quality issues(‘correction’, ‘remediation’, ‘scrubbing’ or ‘cleansing’)
* To eliminate the cause of a data quality issuesto prevent recurring (‘corrective action’)
* To eliminate the cause of a potential data quality issues(‘preventive action’)
* To deal with the consequences of the data quality issues, e.g., to report data isquality issuessues to data users
* To document actions taken.
Check * To monitor the status of data quality issuesand their resolutions.
* To review the effectiveness of corrective and preventive action.
Act * To adapt corrective and preventive action.

Characteristics

Characteristic Requirements
Severity Data quality issuesare resolved in order of severity.

Relations

Data quality issueis child of issue
Data quality issue is an element of a data quality management system
Data quality issueis one of the principles of adata quality program
Data quality issue can be caused by data entry processes
Data quality issue can be caused bydata migration
Data quality issue is a subject in a data quality service level agreement
Data quality issue is identified by data profiling
Data quality issueis prevented by applyingdata quality rules
Data quality issue is identified and resolved by data stewards
Data quality issue is resolved by data cleansing
Data quality issue is eliminated by corrections
Data quality issue is prevented by corrective actions
Data quality issue is prevented by preventive actions
Data quality issuecan be easiers assessed by data lineage
Data quality issue can be tracked in an incident tracking system
Data quality issueis detected and reported bydata quality monitoring

Data quality issues escalation path

The figure shows a possible escalation path of data quality issues. Figure 2: Data quality issues escalation path.

Story

A customer of the TradeAll trade company complained that he had been delivered an incorrect item. The sales department reported this incident in the Incident Tracking System, which was assigned to the Data Steward. The Data Steward then went to see how this could have happened. He found that the item number did not match the item description and suspected that this was due to a data entry error. Based on the item number, the products were taken from the warehouse.

He corrected the item number (Correction), but to prevent this kind of error, he took the measure that the entry of items was checked by a second person to prevent more incidents (Corrective Action). He also made sure to check for duplicate item numbers in the database (Corrective Action).. The customer was apologised for the error and the correct article was delivered as soon as possible.

References

DAMA (2017). DAMA-DMBOK. Data Management Body of Knowledge. 2nd Edition. Technics Publications Llc. August 2017. Chapter 13 Data Quality, section 2.7.3 Develop Operational Procedures for Managing Data Issues.

DAMA Dictionary of Data Management. 2nd Edition 2011. Technics Publications, LLC, New Jersey.

ISO 9000:2015. Quality Management Systems – Requirements.

ISO 9001:2015. Quality Management Systems – Fundamentals and vocabulary.

data_quality_management_system/data_quality_issue.txt · Last modified: 2023/10/17 15:50 by peter