In today’s fast growing digital world, the web, mobile, social networks and other digital platforms are producing enormous amounts of data that hold intelligence and valuable information. Correctly used it has the power to create sustainable value in different forms for businesses. The commonly used term for this data is Big Data, which includes structured, unstructured and hybrid structured data. However, Big Data is of limited value unless insightful information can be extracted from the sources of data.
The solution is Big Data analytics, and how managers and executives can capture value from this vast resource of information and insights. This book develops a simple framework and a non-technical approach to help the reader understand, digest and analyze data, and produce meaningful analytics to make informed decisions. It will support value creation within businesses, from customer care to product innovation, from sales and marketing to operational performance.
The authors provide multiple case studies on global industries and business units, chapter summaries and discussion questions for the reader to consider and explore. Big Data for Managers also presents small cases and challenges for the reader to work on – making this a thorough and practical guide for students and managers.
"Digitization affects all companies. One of the biggest challenges for business executives is to apply the technical capabilities of Big Data into daily business. With its management perspective, its structured model and several interesting case studies, this book provides very good support for managers in how to use Big Data in their business development."
Mats Abrahamsson, Professor, Linköping University, Sweden
"Big Data for Managers does a great job of introducing analytics concepts for an audience that rapidly needs to understand how big data can both transform their business but, equally, make it irrelevant, fast."
Christopher Ahlberg, CEO Recorded Future and Chairman, Hult International Business School, Boston, US
"A well written book, with a good structure. The contents are well laid out, making it very easy for someone to refer to a certain point. The case studies are valuable – puts Big Data knowledge into application. There is a range of companies, and each case study focuses on a certain efficiency Big Data usage has brought about, with a clear structure of background, opportunities, methods and results."
Manoj Gupta, Vice President, HCL Technologies, UK
"Proven use cases from different industries will help business managers, charting clear path towards data driven work culture in their organizations."
Mahendra K. Upadhyay, Head of Data & Technology, Mindshare India
"In a data-driven era, this book is an excellent overview everything that you must know about big data analytics."
Amit Chandak, CTO, Progen Business Solution (BI), India
Table of Contents, Dedication, Acknowledgements , Foreword by Tom Davenport , Chapter 1 – Introduction , For Practicing Manager , A Non-technical book , Structure of the book , Chapter 2 – Big Data Revolution , Data driven decisions and value creation , History of Data and Big Data , Data and Analysis , Data Analysis and Statistics , Data Analysis and Computing , Google Web Search , Big Data Analysis on the Cloud , Structured Data , Unstructured Data , Big Data , Summary , Chapter 3 - Creating Value from Big Data , Value Drivers in commercial organizations , Market Value and Non-Financial Values , Investments where Big Data can create value , Summary , Chapter 4 - Big Data Techniques and Solutions , Big Data Analytics, Data Analytics Techniques , Summary , , , Chapter 5 - Introducing the Model – Design and Implementation , C-ADAPT model of Big Data value creation , C-ADAPT Worksheet , Summary , Chapter 6 - Big Data Case Studies , Ooredoo (formerly Qtel) , Domino’s pizza , Leading Antivirus Company , Gate Gourmet , Tesco , Delta Airlines , Intel , TXU Energy , OmedaRx , John Deere , Airbnb , Walmart , Huffington Post , Summary , Chapter 7 – What Practitioners Say? , Big Data is Important – very important! , Key value from Big Data , Challenges in implementing Big Data projects , Summary , Chapter 8 – Conclusion and Discussion , , References, Index.