Big Data Demystified: How To Use Big Data, Data Science and Ai To Make Better Business Decisions and Gain Competitive Advantage, 1st edition

Published by Pearson (February 12, 2018) © 2019
David Stephenson

Title overview

'Big Data' refers to a new class of data, to which 'big' doesn't quite do it justice. Much like an ocean is more than simply a deeper swimming pool, big data is fundamentally different to traditional data and needs a whole new approach.

Packed with examples and case studies, this clear, comprehensive book will show you how to accumulate and utilise 'big data' in order to develop your business strategy. Big Data Demystified is your practical guide to help you draw deeper insights from the vast information at your fingertips; you will be able to understand customer motivations, speed up production lines, and even offer personalised experiences to each and every customer.

With 20 years of industry experience, David Stephenson shows how big data can give you the best competitive edge, and why it is integral to the future of your business.

Table of contents

  • Part 1 Big data demystified
  • 1 The story of big data
  • 2 Artificial intelligence, machine learning and big data
  • 3 Why is big data useful?
  • 4 Use cases for (big) data analytics
  • 5 Understanding the big data ecosystem
  • Part 2 Making the big data ecosystem work for your organization
  • 6 How big data can help guide your strategy
  • 7 Forming your strategy for big data and data science
  • 8 Implementing data science – analytics, algorithms and machine learning
  • 9 Choosing your technologies
  • 10 Building your team
  • 11 Governance and legal compliance
  • 12 Launching the ship – successful deployment in the organization
  • References
  • Glossary

Author bios

David Stephenson is an internationally recognized expert and frequent keynote speaker in the fields of Data Science and Big Data Analytics.  He has formed and led global analytics programs within US and European companies (including eBay and Axel Springer) and has consultant on additional data projects for a broad range of companies. 

 

He has also worked extensively in insurance, capital markets, and financial risk management and has served as an expert advisor to top-tier investment, private equity and management consulting firms.

 

David completed his Ph.D. at Cornell University and was subsequently Professor at the University of Pennsylvania, teaching applied analytics to graduate students in the engineering and Wharton business schools. He is currently based in Amsterdam.

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