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Data Quality - IntroductionData Quality for professionals. Back to basics.
http://www.prodataquality.com/
Data Quality for professionals. Back to basics.
http://www.prodataquality.com/
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Data Quality - Introduction | prodataquality.com Reviews
https://prodataquality.com
Data Quality for professionals. Back to basics.
prodataquality.com
Data Quality - The Data Layer
http://www.prodataquality.com/TheDataLayer.html
Data Quality Control Cycle. Data Quality Data Rules.
Data Quality Profile
http://www.prodataquality.com/DataQualityProfile.html
The two ways to assess the quality of data sources are:. If we want to profile or scan data we preferrably should use a complete dataset with no restrictions applied to data sources and selected rows. If for some reason we need to assess a data subset (a sample) we have to keep in mind that the selected data set needs to be:. Representative (in size and diversity). Recognizable (data is not scrambled, anonymous or obfuscated). Consistent in subject area (key entity plus all related entities).
Data Quality - Introduction
http://www.prodataquality.com/index.html
Data Quality Control Cycle. Data Quality Data Rules.
Data Quality Criteria
http://www.prodataquality.com/DataQualityBasics.html
The main Data Quality criteria Availability, Usability and Reliability can be further detailed as described below. The final step is to define measurable criteria and metrics to express the Data Quality level. However, there is no such thing as absolute Data Quality. Data Quality must allways be seen in the context of data usage and therefore can be described as fit for use . Data Quality Control Cycle. Data Quality Data Rules.
Data Quality Control Cycle
http://www.prodataquality.com/DataQualityControlCycle.html
Data Quality Control Cycle. Data Quality Control Cycle. Data Quality Data Rules.
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