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

ISBN: 978-1-118-89062-2

October 2016

350 pages

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 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.

About the Author

Ron S. Kenett is chairman of the KPA Group; research professor, University of Turin, Italy, visiting professor at the Hebrew University Institute for Drug Research, Jerusalem, Israel and at the Faculty of Economics, Ljubljana University, Slovenia. He is past president of the Israel Statistical Association (ISA) and of the European Network for Business and Industrial Statistics (ENBIS). Ron authored and co-authored over 200 papers and 12 books on topics ranging from industrial statistics, customer surveys, multivariate quality control, risk management and statistical methods in healthcare up to performance appraisal systems and integrated management models.  The KPA Group he formed in 1990 is a leading Israeli firm focused on generating insights through analytics with international customers such as hp, 3M, Teva, Perrigo, Roche, Intel, Amdocs, Stratasys, Israel Aircraft Industries, The Israel Electricity Corporation,  ICL, start ups, banks and health care providers. He was awarded the 2013 Greenfield Medal by the Royal Statistical Society in recognition for excellence in contributions to the applications of Statistics. Among his many activities he is member of the National Public Advisory Council for Statistics Israel, member of the Executive Academic Council, Wingate Academic College and board member of several pharmaceutical and Internet product companies.

Galit Shmueli is distinguished professor at National Tsing Hua University’s Institute of Service Science. She is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored and co-authored over 70 journal articles, book chapters, books, and textbooks, including Data Mining for Business Intelligence, Modeling Online Auctions, and Getting Started with Business Analytics. Her research is published in top journals in Statistics, Management, Marketing, Information Systems, and more. Professor Shmueli has designed and instructed business analytics courses and programs since 2004 at University of Maryland, The Indian School of Business, Statistics.com, and National Tsing Hua University, Taiwan. She has also taught engineering statistics courses at the Israel Institute of Technology and at Carnegie Mellon University.