Fr. 76.00

Data Mining and Market Intelligence - Implications for Decision Making

English · Paperback / Softback

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Description

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This book is written to address the issues relating to data gathering, data warehousing, and data analysis, all of which are useful when working with large amounts of data. Using practical examples of market intelligence, this book is designed to inspire and inform readers on how to conduct market intelligence by leveraging data and technology, supporting smart decision making. The book explains some suitable methodologies for data analysis that are based on robust statistical methods. For illustrative purposes, the author uses real-life data for all the examples in this book. In addition, the book discusses the concepts, techniques, and applications of digital media and mobile data mining.
Hence, this book is a guide tool for policy makers, academics, and practitioners whose areas of interest are statistical inference, applied statistics, applied mathematics, business mathematics, quantitative techniques, and economic and social statistics.

List of contents

Foreword.- Preface.- Acknowledgments.- Acronyms.- Introduction to Market Intelligence.- The Market Research Process.- Qualitative Techniques.- Quantitative Techniques.- Hypothesis Testing and Regression Analysis.- Analyzing Survey Data.- Index Methodology.- Digital Media Monitoring, Measurement, and Modeling.- Causal Methods.- Mobile Data Mining.- Bibliography.- Author's Biography.

About the author










Dr. Mustapha Akinkunmi is a Financial Economist and Technology Strategist. He has over 25 years of experience in estimation, planning, and forecasting using statistical and econometric methods, with particular expertise in risk, expected utility, discounting, binomial-tree valuation methods, financial econometrics models, Monte Carlo simulations, macroeconomics, and exchange rate modeling. Dr. Akinkunmi has performed extensive software development for quantitative analysis of capital markets, revenue and payment gateway, predictive analytics, data science, and credit risk management. He has a record of success in identifying and implementing change management programs and institutional development initiatives in both public and private sector organizations. He has been in high profile positions as a Consultant, Financial Advisor, Project Manager, and Business Strategist to AT&T, Salomon Brothers, Goldman Sachs, Phibro Energy, First Boston (Credit Suisse First Boston), World Bank, and Central Bank of Nigeria. He is an internationally recognized co-author (Introduction to Strategic Financial Management, May 2013) and leader in demand analysis, specializing in working with very large databases. Furthermore, he has conducted teaching and applied research in areas that include analyses of expenditure patterns, inflation and exchange rate modeling for Manhattan College, Riverdale, NY, Fordham University, New York, NY, University of Lagos, Lagos, Nigeria, State University of New York-FIT, New York, NY, Montclair State University, Montclair, NJ, and American University, Yola, Nigeria. In 1990, he founded Technology Solutions Incorporated (TSI) in New York, which focused on data science and software application development for clients including major financial services institutions. After ten years of successful operations and rapid growth under Dr. Akinkunmi's leadership, TSI was acquired by a publicly traded technology company based in the U.S. in a value-creating transaction. Dr. Akinkunmi was the former Honorable Commissioner for Finance, Lagos State, Nigeria. He is now an associate professor of finance and chair of the accounting and finance department at the American University of Nigeria, Yola, Nigeria.

Product details

Authors Mustapha Akinkunmi
Publisher Springer, Berlin
 
Original title Data Mining and Market Intelligence
Languages English
Product format Paperback / Softback
Released 01.01.2018
 
EAN 9783031793899
ISBN 978-3-0-3179389-9
No. of pages 159
Dimensions 191 mm x 10 mm x 235 mm
Illustrations XXII, 159 p.
Series Synthesis Lectures on Engineering
Subject Natural sciences, medicine, IT, technology > Technology > Mechanical engineering, production engineering

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