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Big Data Analytics: Turning Big Data into Big Money by Frank J. Ohlhorst

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Contents

Preface

Acknowledgments

Chapter 1: What is Big Data?

The Arrival of Analytics

Where is the Value?

More to Big Data Than Meets the Eye

Dealing with the Nuances of Big Data

An Open Source Brings Forth Tools

Caution: Obstacles Ahead

Chapter 2: Why Big Data Matters

Big Data Reaches Deep

Obstacles Remain

Data Continue to Evolve

Data and Data Analysis are Getting More Complex

The Future is Now

Chapter 3: Big Data and the Business Case

Realizing Value

The Case for Big Data

The Rise of Big Data Options

Beyond Hadoop

With Choice Come Decisions

Chapter 4: Building the Big Data Team

The Data Scientist

The Team Challenge

Different Teams, Different Goals

Don’t Forget the Data

Challenges Remain

Teams versus Culture

Gauging Success

Chapter 5: Big Data Sources

Hunting for Data

Setting the Goal

Big Data Sources Growing

Diving Deeper into Big Data Sources

A Wealth of Public Information

Getting Started with Big Data Acquisition

Ongoing Growth, No End in Sight

Chapter 6: The Nuts and Bolts of Big Data

The Storage Dilemma

Building a Platform

Bringing Structure to Unstructured Data

Processing Power

Choosing among In-house, Outsourced, or Hybrid Approaches

Chapter 7: Security, Compliance, Auditing, and Protection

Pragmatic Steps to Securing Big Data

Classifying Data

Protecting Big Data Analytics

Big Data and Compliance

The Intellectual Property Challenge

Chapter 8: The Evolution of Big Data

Big Data: The Modern Era

Today, Tomorrow, and the Next Day

Changing Algorithms

Chapter 9: Best Practices ...

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