Matches in DBpedia 2015-10 for { ?s ?p "Data quality assessment is the process of exposing technical and business data issues in order to plan data cleansing and data enrichment strategies. Technical quality issues are generally easy to discover and correct, such as: Inconsistent standards in structure, format/ values Missing data, default values Spelling errors, data in wrong fieldsBusiness quality issues are more subjective and are associated with business processes such as generating accurate reports, ensuring that data driven processes are working correctly.Business data quality measures like accuracy and correctness are subjective and need Subject Matter Expert (SME) involvement to assess data quality."@en }
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- Data_quality_assessment abstract "Data quality assessment is the process of exposing technical and business data issues in order to plan data cleansing and data enrichment strategies. Technical quality issues are generally easy to discover and correct, such as: Inconsistent standards in structure, format/ values Missing data, default values Spelling errors, data in wrong fieldsBusiness quality issues are more subjective and are associated with business processes such as generating accurate reports, ensuring that data driven processes are working correctly.Business data quality measures like accuracy and correctness are subjective and need Subject Matter Expert (SME) involvement to assess data quality.".