Data Quality
What is Data Quality?
The degree to which data meets the requirements for its intended use in terms of accuracy, completeness, consistency, timeliness, and validity.
Terms that appear alongside data quality
Each of these is named in at least one of the same controls as data quality. The number is how many controls name both.
- audit 13 shared controls
- quality management 13 shared controls
- governance 11 shared controls
- compliance 9 shared controls
- accountability 9 shared controls
- transparency 8 shared controls
- consent 7 shared controls
- integrity 7 shared controls
Frameworks that govern data quality
What the standards actually require on data quality
Requirements naming data quality across 6 standards, quoted from the control text.
Check during and after processing whether data conform to requirements, and act to control them when nonconformities turn up; 6.1 gives this work to data quality specialists. ISO 8000-62 assigns it to maturity Level 2 (Managed).
iso-8000-data-quality::61:6.3.4 · 6.3.4 Data Quality Monitoring and Control (DQC.3) →Data quality is measured and judged in a systematic way, using defined processes and techniques and testing the data against its quality rules.
cobit-2019::APO14.06 · APO14.06 Ensure a data quality assessment approach →Profile and assess the critical data against the rules to establish the baseline and the issues.
dama-dmbok2-data-management-body-of-knowledge-2nd-edition::DQ.2.4 · DQ.2.4 Perform an initial data quality assessment →Approved policy, standards and procedures for managing data quality issues apply consistently on-premises and in the cloud; issue reporting is integrated across environments; every issue is linked to the specific data asset and its catalog metadata;
edm-council-cdmc-cloud-data-management-capability-framework::5.2.4 · 5.2.4 Data Quality Issues are managed →Data quality issues are identified, logged, prioritized and remediated, correcting existing data and performing root-cause analysis to tackle the causes lying beneath, whether in people, process, data or technology, and stop the issue coming back.
edm-council-dcam-data-management-capability-assessment-model::5.4 · 5.4 Data Quality Remediation Management →GS1 implementation roadmap + organizational roles. ROLES: (a) MASTER DATA MANAGER + DATA STEWARD - day-to-day GS1 keys allocation + master data quality + GDSN data publication + maintenance;
GS1-Implementation-Roadmap-Roles-Tooling · GS1 Implementation Roadmap, Organizational Roles, Tooling and Data Quality →Questions people ask about data quality
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