The first five articles in this series contrasted the dimensions of data quality defined by six renowned authors - including valuable points from additional authors as applicable. Clearly there are many valuable aspects to the dimensions of data quality:

The purpose for having an industry-accepted set of dimensions with associated concepts is to allow organizations to effectively communicate internally and externally. In a more networked society, where there are more external demands on our data, such as governmental regulation, legal, security, corporate partnerships and corporate valuation, agreed-upon standards are a must. In a recent discussion on this topic with data quality author Danette McGilvray, she pointed out that from an internal perspective, the quicker an organization can establish and start using these foundational dimensions, the sooner they will see the benefits. Why not get a jump-start using the industry standard and then add custom categories and concepts as needed?

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