The Impact of Data Governance and Data Quality on MDM
Solving data quality and governance issues requires change and changing a stable system requires motivation. While there is very little doubt that the financial cost of data that does not meet requirements is huge, data errors are also a source of embarrassment, distress, suffering and lost opportunity. Every event, every individual, every organization, as well as goods and services are represented by data. That data may be considered good data but that does not guarantee it is good information. Quality information can only be based on quality data. The data must meet the requirements for which it is intended to be used before we can process and label it in a way that gives it meaning. It is important to remember that data is a business tool and knowing what data to collect, when to collect it, and how to use the data is actually more important than the data itself.
Peter R. Benson is the author of Managing Blind; a Data Quality and Data Governance Vade Mecum and the project leader for ISO 8000, the international standard for data quality. Peter has wide practical experience taken from his thirty-year carrier in analyzing and resolving data quality and data governance challenges in the defense, aerospace, agriculture, mining, oil and gas, industrial manufacturing and processing as well as in the finance, insurance and health care industries.
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