Big Data, Big Analytics
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Big Data, Big Analytics Emerging Business Intelligence and Analytic Trends for Today's Businesses

Edited by Michael Minelli · Michele Chambers · Ambiga Dhiraj
John Wiley & Sons January 2013

Specifications

ISBN-13
9781118147603
Publisher
John Wiley & Sons
Publication
January 2013
Format
Hardback , 187 pages
Jurisdiction
International ? Countri(es) for reference only

Details

Unique prospective on the big data analytics phenomenon for both business and IT professionals

The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability.

The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics.

  • Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.)
  • Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights
  • Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.

Table of Contents

Foreword

Preface

Acknowledgments

Chapter 1 What Is Big Data and Why Is It Important?

A Flood of Mythic “Start-up” Proportions

Big Data is More Than Merely Big

Why Now?

A Convergence of Key Trends

Relatively Speaking…

A Wider Variety of Data

The Expanding Universe of Unstructured Data

Setting the Tone at the Top

Notes

Chapter 2 Industry Examples of Big Data

Digital Marketing and the Non-line World

Don’t Abdicate Relationships

Is IT Losing Control of Web Analytics?

Database Marketers, Pioneers of Big Data

Big Data and the New School of Marketing

Fraud and Big Data

Risk and Big Data

Credit Risk Management

Big Data and Algorithmic Trading

Calculating Risk in Marketing

Other Industries Benefit from Banking’s Risk Experience

Big Data and Advances in Healthcare

“Disruptive Analytics”

A Holistic Value Proposition

BI is not Data Science

Pioneering New Frontiers in Medicine

Advertising and Big Data: From Papyrus to Seeing Somebody

Big Data Feeds the Modern Day Draper

Measurement Can Be Tricky

Beard’s Take on the Three Big Data V’s in Advertising

Using Consumer Products as a Doorway

Notes

Chapter 3 Big Data Technology

The Elephant in the Room: Hadoop’s Parallel World

Old versus New Approaches

Data Discovery: Work the Way People’s Minds Work

Open Source Technology for Big Data Analytics

The Cloud and Big Data

Predictive Analytics Moves into the Limelight

Software as a Service BI

Mobile Business Intelligence is Going Mainstream

Ease of Mobile Application Deployment

Crowdsourcing Analytics

Inter and Trans Firewall Analytics

R&D Approach Helps Adopt New Technology

Adding Big Data Technology into the Mix

Big Data Technology Terms

Data Size 101

Notes

Chapter 4 Information Management

The Big Data Foundation

Big Data Computing Platforms (or Computing Platforms that can handle the Big Data Analytics Tsunami)

Big Data Computation

More on Big Data Storage

Big Data Computational Limitations

Big Data Emerging Technologies

Chapter 5 Business Analytics

The Last Mile in Data Analysis

Listening: Is it Signal or Noise?

Consumption of Analytics

From Creation to Consumption

Visualizing: How to Make It Consumable?

Organizations are using Data Visualization as a Way to Take Immediate Action

Moving from Sampling to Using All the Data

Thinking Outside the Box

360 Degree Modeling

Need for Speed

Let’s Get Scrappy

What Technology is Available?

Moving from beyond the Tools to Analytic Applications

Notes

Chapter 6 The People Part of the Equation

Rise of the Data Scientist

Learning over Knowing

Using Deep Math, Science and Computer Science

The 90/10 Rule and Critical Thinking

Analytic Talent and Executive Buy-in

Developing Decision Sciences Talent

Holistic View of Analytics

Creating Talent for Decision Sciences

Creating a Culture that Nurtures Decision Sciences Talent

Setting up the Right Organizational Structure for Institutionalizing Analytics

Chapter 7 Data Privacy and Ethics

The Privacy Landscape

The Great Data Grab Isn’t New

Preferences, Personalization, and Relationships

Rights and Responsibility

Playing in a Global Sandbox

Conscientious and Conscious Responsibility

Privacy May Be the Wrong Focus

Can Data Be Anonymized?

Balancing for Counter Intelligence

Now What?

Notes

Conclusion

Recommended Resources

About the Authors

Index

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