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Passionately curious about Data, Databases and Systems Complexity. Data is ubiquitous, the database universe is dichotomous (structured and unstructured), expanding and complex. Find my Database Research at SQLToolkit.co.uk . Microsoft Data Platform MVP

"The important thing is not to stop questioning. Curiosity has its own reason for existing" Einstein



Saturday, 2 May 2020

Data Quality Framework

Data quality is defined as the planning, implementation, and control of activities that apply quality management techniques to data, in order to assure it is fit for consumption and meets the needs of data consumers. (The Data Management Body of Knowledge)

The trustworthiness and quality of our data has real impact in the world and on society influencing critical decisions. To help ensure the data we collect from around us helps answers questions and provide informed answers, a data quality framework is required. There are many components required to help improve data quality.  The Data Quality dimensions that can be measured to manage improvement are:

  • Accuracy
  • Completeness
  • Consistency
  • Integrity
  • Reasonability
  • Timeliness
  • Uniqueness
  • Validity
  • Accessibility

Below is my data quality framework.



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