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- Jan 1, 1970
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Data quality is a critical issue affecting Data Warehouses (DWs) yet there appears to be no sustainable solution with regards to quality input into operational systems that ultimatley feed DWs.
Kimball believes management can play their part by responding to errors highlighted in reports derived from the DW. I'm not sure this works because management invariably have no financial incentive to ensure data input into source systems is always correct.
Has anyone worked in an organisation where a line manager's overall performance is also measured by the quality of data relating to his/her portfolio, highlighted by say data quality audits and error reports derived from the DW?
Could tying bonuses to pre-determined data quality hurdle rates of say 95% for the quality of data under managements control work as incentive to improve data quality at the input end, thereby, allieviating some of the dependency on DW data cleansing tools?
Kimball believes management can play their part by responding to errors highlighted in reports derived from the DW. I'm not sure this works because management invariably have no financial incentive to ensure data input into source systems is always correct.
Has anyone worked in an organisation where a line manager's overall performance is also measured by the quality of data relating to his/her portfolio, highlighted by say data quality audits and error reports derived from the DW?
Could tying bonuses to pre-determined data quality hurdle rates of say 95% for the quality of data under managements control work as incentive to improve data quality at the input end, thereby, allieviating some of the dependency on DW data cleansing tools?