Data quality refers to the tools and processes that result in the creation of correct, complete and valid data that is required to support sound decision-making.


FeatureIn part five of this series, we'll look at two, sometimes forgotten elements of quality data: definition and representation
featureThis article builds on what was discussed in prior articles in this series regarding the dimensions of data quality by looking more closely at Validity and Integrity
BlogCaution on underlying accuracy of recommendation engines
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FeatureIn part three of this series, we’ll look at one of the most foundational dimensions: Completeness
featureBig data has caused a shake-up in established data governance practices
FeatureThis series of articles documents the level of consistency between six authors’ definitions of each of the dimensions of quality. The second of these, “reasonability,” is covered in this article
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BlogDebunking hiring myths, but wary of career-derailing stats
FeatureThe focused effort to manage master data coupled with an organization’s ability to leverage sources of big data, especially social networks, will result in optimized business processes and measurable business performance improvements
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SurveyAs businesses set out to use more analytics to interact with consumers across an average of 3.6 channels, data quality becomes increasingly important, according to Experian QAS
featureThis series of articles documents the level of consistency between six authors’ definitions of each of the dimensions of quality. The first of these, “accuracy,” is covered in this article
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Case StudyWith a master data management framework in place, Toronto-based retailer readies the next stages of its extensive data strategy; team presenting at MDM and Data Governance event in Toronto June 26-27
BlogThree examples when consumer electronics rightly took the low road
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Are you actively evaluating master data management technologies and their ability to scale and support emerging trends around big data, social and mobile?

Yes 61%
No 23%
Don't Know 9%
Not Applicable 6%

 

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