Big Data Revolution E-Book

Rob Thomas

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch
• Veröffentlichungsjahr: 2015

Seitenzahl: 418

Beschreibung

Exploit the power and potential of Big Data to revolutionize business outcomes Big Data Revolution is a guide to improving performance, making better decisions, and transforming business through the effective use of Big Data. In this collaborative work by an IBM Vice President of Big Data Products and an Oxford Research Fellow, this book presents inside stories that demonstrate the power and potential of Big Data within the business realm. Readers are guided through tried-and-true methodologies for getting more out of data, and using it to the utmost advantage. This book describes the major trends emerging in the field, the pitfalls and triumphs being experienced, and the many considerations surrounding Big Data, all while guiding readers toward better decision making from the perspective of a data scientist. Companies are generating data faster than ever before, and managing that data has become a major challenge. With the right strategy, Big Data can be a powerful tool for creating effective business solutions - but deep understanding is key when applying it to individual business needs. Big Data Revolution provides the insight executives need to incorporate Big Data into a better business strategy, improving outcomes with innovation and efficient use of technology. * Examine the major emerging patterns in Big Data * Consider the debate surrounding the ethical use of data * Recognize patterns and improve personal and organizational performance * Make more informed decisions with quantifiable results In an information society, it is becoming increasingly important to make sense of data in an economically viable way. It can drive new revenue streams and give companies a competitive advantage, providing a way forward for businesses navigating an increasingly complex marketplace. Big Data Revolution provides expert insight on the tool that can revolutionize industries.

Leseprobe

This edition first published 2015© 2015 John Wiley and Sons, Ltd.

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ISBN 978-1-118-94371-7 (paperback); 978-1-118-94373-1 (ePDF); 978-1-118-94372-4 (ePub)

Set in 9.5/11.5 MinionPro-Regular by SPS/TCS

Printed in U.S. by Bind Rite Robbinsville

This book is for those who are willing to lead, in any endeavor. Most of all, this book is for Kristin, Will, Abby, and Sam. And, a special thanks to my big sister.

— Rob Thomas

To my parents Agnes and Patrick, wife Emmeline, and children Isolde, Theodore and Caspian.

— Patrick McSharry

About the Authors

Rob Thomas is Vice President of Product Development for Big Data and Information Management in the IBM Software Group. With over 15 years in the technology industry, Mr. Thomas has had the opportunity to consult to a variety of global businesses. He has experience in business and operational strategy, high technology, acquisitions and divestitures, manufacturing operations, and product design and development.

Mr. Thomas is currently responsible for product development and engineering for IBM’s Big Data and Information Management product line. As Vice President of Business Development in IBM Software, Mr. Thomas led the acquisition of Netezza and Vivisimo, both leaders in the data era.

Mr. Thomas has extensive international experience, leading IBM’s high technology services business in Asia Pacific, while living in Tokyo, Japan. Prior to that, he was a Partner in IBM’s consulting business.

Mr. Thomas graduated from Vanderbilt University with a BA in Economics. He earned his Masters in Business Administration from the University of Florida. Mr. Thomas publishes regularly on his blog (http://www.robdthomas.com) and has an active following on Twitter (@robdthomas). He is an avid golfer, reader, and exercise enthusiast. He lives in New Canaan, Connecticut with his wife (Kristin) and three children (Will, Abby, and Sam).

Most of what he has learned in his life came from his parents, his wife, and his two sisters.

Patrick McSharry is a Senior Research Fellow at the Smith School of Enterprise and the Environment, Faculty Member of the Oxford Man Institute of Quantitative Finance at Oxford University, Visiting Professor at the Department of Electrical and Computer Engineering, Carnegie Mellon University, Fellow of the Royal Statistical Society and Senior Member of the IEEE. He takes a multidisciplinary approach to developing quantitative techniques for data science, decision-making, and risk management. His research focuses on big data, forecasting, predictive analytics, machine learning, and the analysis of human behavior. He has published over 90 peer-reviewed papers, participated in knowledge exchange programs and consults for national and international government agencies and the insurance, finance, energy, telecoms, environment, and healthcare sectors. Patrick received a first class honours BA in Theoretical Physics and an MSc in Engineering from Trinity College Dublin and a DPhil in Mathematics from Oxford University.

About the Technical Editor

Carin Anderson is a freelance technical editor. She has edited, compiled, and written numerous grants and proposals over the last decade and a half. Carin developed a mobile application company, creating multi-user gaming platforms. She also co-founded an informational website targeting families with young children.

In her spare time, she enjoys spending time with her family and friends, running and reading.

PUBLISHER’S ACKNOWLEDGEMENTS

Some of the people who helped bring this book to market include the following:

Editorial and Production

VP Consumer and Technology Publishing Director: Michelle Leete

Associate Director–Book Content Management: Martin Tribe

Professional Technology & Strategy Director: Barry Pruett

Commissioning Editor: Ellie Scott

Development Editor: Tom Dinse

Copy Editor: Laura Miller

Technical Editor: Carin Anderson

Marketing

Associate Marketing Director: Louise Breinholt

Marketing Manager: Lorna Mein

Marketing Executive: Polly Thomas

Composition Services

Proofreader: Wordsmith Editorial

Indexer: Potomac Indexing, LLC

Big Data Revolution

Table of Contents

Prologue

Berkeley, 1930s

Pattern Recognition

Nelson Peltz

Committing to One Percent

The Big Data Revolution

Introduction

Storytelling

Objective

Outline

Part I “The Revolution Starts Now: 9 Industries Transforming with Data”

Part II “Learning from Patterns in Big Data”

Part III “Leading the Revolution”

Storytelling (Continued)

Part I: The Revolution Starts Now: 9 Industries Transforming with Data

Chapter 1: Transforming Farms with Data

California, 2013

Brief History of Farming

The Data Era

Potato Farming

Precision Farming

Capturing Farm Data

Deere & Company Versus Monsanto

Integrated Farming Systems

Data Prevails

The Climate Corporation

Growsafe Systems

Farm of the Future

California, 2013 (Continued)

Chapter 2: Why Doctors Will Have Math Degrees

United States, 2014

The history of Medical Education

Scientific Method

Rise of Specialists

We have a Problem

Ben Goldacre

Vinod Khosla

The Data Era

Collecting Data

Telemedicine

Innovating with Data

Implications of a Data-Driven Medical World

The Future of Medical School

A Typical Medical School

A Medical School for the Data Era

United States, 2030

Chapter 3: Revolutionizing Insurance: Why Actuaries Will Become Data Scientists

Middle of Somewhere, 2012

Short History of Property & Casualty Insurance and Underwriting

Actuarial Science In Insurance

Pensions, Insurance, Leases

Compound Interest

Probability

Mortality Data

Modern-Day Insurance

Eight Weeks to Eight Days

Online Policies

The Data Era

Dynamic Risk Management

Catastrophe Risk

Open Access Modeling

Opportunities

Middle of Somewhere, 2012 (Continued)

Chapter 4: Personalizing retail and fashion

Karolina

A Brief History of Retail

Retail Eras

Aristide Boucicaut

The Shift

The Data Era

Stitch Fix

Keaton Row

Zara

Karolina (Continued)

Chapter 5: Transforming Customer relationships with data

Buying a House

Brief History of Customer Service

Customer Service Over Time

Boeing

Financial Services

The Data Era

An Automobile Manufacturer

Zendesk

Buying a House (Continued)

Chapter 6: Intelligent Machines

Denmark

Intelligent Machines

Machine Data

The Data Era

General Electric

Drones

Tesla

Networks of Data

Denmark (Continued)

Chapter 7: Government and Society

Egypt, 2011

Social Media

Intelligence

Snowden Effect

Privacy Risk Versus Reward

Observation or Surveillance

Development Targets

Open Data

Hackathons

Open Access

Ensuring Personal Protection

Private Clouds

Sanitizing Data

Evidence-Based Policy

Public-Private Partnerships

Impact Bonds

Social Impact Bond

Development Impact Bonds

The Role of Big Data

Egypt, 2011 (Continued)

Chapter 8: Corporate Sustainability

City of London

Global Megaforces

Population

Carbon Footprint

Water Scarcity

Environmental Risk

BP and Exxon Mobile

Early Warning Systems

Social Media

Risk and Resilience

Measuring Sustainability

Long-Term Decision Making

Stranded Assets

City of London (Continued)

Chapter 9: Weather and Energy

India, 2012

The Weather

Forecasting the Weather

When are Weather Forecasts Wrong?

Chaos

Ensemble Forecasts

Communication

Renewable Energy

Solar, Hydro, and Wind Power

Volatile or Intermittent Supply

Energy Consumption

Smart Meters

Intelligent Demand-Side Management

India, 2012 (Continued)

Part II: Learning from Patterns in Big Data

Chapter 10: Pattern Recognition

Elements of Success Rhyme

Pattern Recognition: A Gift or Trap?

What Fish Teach us about Pattern Recognition

Bayes’ Theorem

Tsukiji Market

Pattern Recognition

Rochester Institute of Technology

A Method for Recognizing Patterns

Elements of Success Rhyme (Continued)

Chapter 11: Why Patterns in Big Data Have Emerged