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> > 컴퓨터 일반도서 > Databases > Data Warehousing

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Big Data Analytics: Turning Big Data into Big Money
출판사 : Wiley
저 자 : Ohlhorst
ISBN : 9781118147597
발행일 : 2011-12
도서종류 : 외국도서
발행언어 : 영어
페이지수 : 160
판매가격 : 49,000원
판매여부 : 재고확인요망
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   Big Data Analytics: Turning Big Data into Big Money 목차
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 Modern 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

Appendix Supporting Data 125

“The MapR Distribution for Apache Hadoop” 126

“High Availability: No Single Points of Failure” 142

About the Author 151

Index 153
   도서 상세설명   

Think bigger and see bigger returns with Big Data Analytics

You're sitting on a gold mine. Buried deep within your backup, in your data archives, or in the data sets right under your nose, are the secrets to increasing your revenue, finding new business relationships, and making more intuitive decisions that will take your organization to the next level. In Big Data Analytics, you'll discover how to harness, analyze, and leverage your data to see big returns to your bottom line.

Author Frank Ohlhorst shares his decades of technical experience to show you how to implement Big Data analytics into any size business or industry. In Big Data Analytics, you'll discover how to mine the value of the data, expose trends that can be converted into competitive strategies, and explore data sources in more interesting and applicable ways to develop intelligence that solves problems and increases profits, productivity, and business opportunities.

Exploring the concepts behind Big Data, how to analyze that data, and the payout you can achieve from acting on your data, Big Data Analytics reveals:

The 4Vs of Big Data and the intrinsic value of each
Big Data and the business case: beyond Hadoop
Building the Big Data dream team
Choosing among in-house, outsourced, or hybrid approaches
The evolution of Big Data: today, tomorrow, and the next day
Best and worst practices
Bringing it all together
Any organization looking to stay ahead of the pack needs to get its arms around Big Data today. Learn how to make your data a key component of your growth strategy with Big Data Analytics.

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