Book description
Provides an important framework for data analysts in assessing the quality of data and its potential to provide meaningful insights through analysis Analytics and statistical analysis have become pervasive topics, mainly due to the growing availability of data and analytic tools. Technology, however, fails to deliver insights with added value…
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Why read it?
1 author picked Information Quality as one of their favorite books. Why do they recommend it?
A lightly technical introduction to a comprehensive framework defining and evaluating the quality of information generated by statistical analysis. It expands the role of analytics by including dimensions that affect information quality such as data resolution, data integration, operationalization, and generalizability of findings. This wide-angle perspective provides a practical checklist that has been found useful in applications. Multiple case studies enable the reader to connect to his favorite topic, but also learn from other areas.
From Ron's list on The best books on how numbers turn into information: the challenge of analytics.
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