Information Quality: The Potential of Data and Analytics to Generate Knowledge

  Ron S. Kenett, Chairman and CEO of KPA Ltd. also Research Professor, University of Turin, Italy and International Professor, NYU School of Engineering, New York, USAGalit Shmueli, Institute of Service Science, National Tsing Hua University, Taiwan 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 if the quality of the information it generates is not assured. Information Quality (InfoQ) is a tool developed by the authors to assess the potential of a dataset to achieve a goal of interest, using data analysis.  Whether the information quality of a dataset is sufficient is of practical importance at many stages of the data analytics journey, from the pre–data collection stage to the post–data collection and post–analysis stages. It is also critical to various stakeholders: data collection agencies, analysts, data scientists, and management.  This book: Explains how to integrate the notions of goal, data, analysis and utility that are the main building blocks of data analysis within any domain. Presents a framework for integrating domain knowledge with data analysis. Provides a combination of both methodological and practical aspects of data analysis. Discusses issues surrounding the implementation and integration of InfoQ in both academic programmes and business / industrial projects. Showcases numerous case studies in a variety of application areas such as education, healthcare, official statistics, risk management and marketing surveys. Presents a review of software tools from the InfoQ perspective along with example datasets on an accompanying website.  This book will be beneficial for researchers in academia and in industry, analysts, consultants, and agencies that collect and analyse data as well as undergraduate and postgraduate courses involving data analysis. INDICE: Dedication .List of contributors .About the Editors .Foreword .Preface .About the Companion Website .Part I: The Information Quality Framework .1. Introduction to information quality .2. Quality of data, quality of analysis .3. The dimensions of InfoQ .4. InfoQ at the study–design stage .5. InfoQ at the post–data collection stage .Part II: Applications of InfoQ .6. Education .7. Customer surveys .8. Healthcare .9. Risk management .10. Official statistics .Part III: Implementing InfoQ .11. InfoQ and reproducible research .12. InfoQ in review processes of scientific publications .13. Integrating InfoQ into applied statistics and data mining academic programs .14. Information quality support with R .15. Information quality support with MINITAB .16. Information quality support with JMP .Index

• ISBN: 978-1-118-87444-8
• Editorial: Wiley–Blackwell
• Encuadernacion: Cartoné
• Páginas: 384
• Fecha Publicación: 18/11/2016
• Nº Volúmenes: 1
• Idioma: Inglés