Big data analytics : turning big data into big money / Frank Ohlhorst.

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Bibliographic Details
Main Author: Ohlhorst, Frank, 1964-
Language:English
Published: Hoboken, N.J. : Wiley, [2013], ©2013.
Series:Wiley and SAS business series.
Subjects:
Business intelligence.
Data mining.
Physical Description:xiv, 160 pages : illustrations ; 24 cm.
Format: Book
Contents:
  • Chapter 1 What Is Big Data? 1
  • The Arrival of Analytics 2
  • Where Is the Value? 3
  • More to Big Data Than Meets the Eye 5
  • Dealing with the Nuances of Big Data 6
  • An Open Source Brings Forth Tools 7
  • Caution: Obstacles Ahead 8
  • Chapter 2 Why Big Data Matters 11
  • Big Data Reaches Deep 12
  • Obstacles Remain 13
  • Data Continue to Evolve 15
  • Data and Data Analysis Are Getting More Complex 17
  • The Future Is Now 18
  • Chapter 3 Big Data and the Business Case 21
  • Realizing Value 22
  • The Case for Big Data 22
  • The Rise of Big Data Options 25
  • Beyond Hadoop 27
  • With Choice Come Decisions 28
  • Chapter 4 Building the Big Data Team 29
  • The Data Scientist 29
  • The Team Challenge 30
  • Different Teams, Different Goals 31
  • Don't Forget the Data 32
  • Challenges Remain 32
  • Teams versus Culture 34
  • Gauging Success 35
  • Chapter 5 Big Data Sources 37
  • Hunting for Data 38
  • Setting the Goal 39
  • Big Data Sources Growing 40
  • Diving Deeper into Big Data Sources 42
  • A Wealth of Public Information 43
  • Getting Started with Big Data Acquisition 44
  • Ongoing Growth, No End in Sight 46
  • Chapter 6 The Nuts and Bolts of Big Data 47
  • The Storage Dilemma 47
  • Building a Platform 52
  • Bringing Structure to Unstructured Data 57
  • Processing Power 59
  • Choosing among In-house, Outsourced, or Hybrid Approaches 61
  • Chapter 7 Security, Compliance, Auditing, and Protection 63
  • Pragmatic Steps to Securing Big Data 64
  • Classifying Data 65
  • Protecting Big Data Analytics 66
  • Big Data and Compliance 67
  • The Intellectual Property Challenge 72
  • Chapter 8 The Evolution of Big Data 77
  • Big Data: The Modem Era 80
  • Today, Tomorrow, and the Next Day 84
  • Changing Algorithms 90
  • Chapter 9 Best Practices for Big Data Analytics 93
  • Start Small with Big Data 94
  • Thinking Big 95
  • Avoiding Worst Practices 96
  • Baby Steps 98
  • The Value of Anomalies 101
  • Expediency versus Accuracy 103
  • In-Memory Processing 104
  • Chapter 10 Bringing It All Together 111
  • The Path to Big Data 112
  • The Realities of Thinking Big Data 113
  • Hands-on Big Data 115
  • The Big Data Pipeline in Depth 116
  • Big Data Visualization 121
  • Big Data Privacy 122.