Big Data Analytics: Turning Big Data into Big Money
Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportunities.
- Reveals big data analytics as the next wave for businesses looking for competitive advantage
- Takes an in-depth look at the financial value of big data analytics
- Offers tools and best practices for working with big data
Once the domain of large on-line retailers such as eBay and Amazon, big data is now accessible by businesses of all sizes and across industries. From how to mine the data your company collects, to the data that is available on the outside, Big Data Analytics shows how you can leverage big data into a key component in your business's growth strategy.
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
FRANK J. OHLHORST is an award-winning technology journalist, professional speaker, and IT business consultant with over twenty-five years of experience in the technology arena. He has written for several leading technology publications, speaks at many industry conferences, and has several industry certifications.
New book brings unique insights to implementing big data analytics and reaping big returns to your bottom line.
Several very large businesses and enterprises have been using Big Data to improve their bottom lines – examples include Amazon’s predictive buying algorithms, EBay’s auction recruitment system, and major airlines determining travel trends. Those examples prove that dissociative data analysis across major data stores can expose trends that can be converted into competitive strategies.
Big Data Analytics: Turning Big Data into Big Money (Wiley; November 2012; ISBN: 978-1-1181-4759-7; 160 pages; Hardcover; US$49.95) will focus on the business and financial value of big data analytics, demonstrate the importance of analytics, define the processes, highlight the tangible and intangible values and discuss how to turn a business liability (large scale data storage, backup and archiving) into actionable material that can be used to redefine markets, improve profits and identify new business opportunities.
Written by Frank J. Ohlhorst, award winning technology journalist, professional speaker and IT business consultant with over 25 years of experience in the technology arena, the book takes an in-depth look at the financial value of big data analytics and offers the tools and best practices for working with big data.
Over the last two years, big data analytics has taken on new roles and is applicable to more and more business types. A sea of change has occurred, that has delivered improved tools (such as Hadoop), access to government data (census, library of congress, GIS), and has delivered platforms that are now accessible to businesses of most any size.
These changes have extended the value of Big Data down the chain, so that small businesses can articulate internal data and combine analytics with public data to devise new algorithms that focus on segmented markets, such as vertical and regional markets.
Therein lies the biggest challenge: How can businesses continue to afford to save massive amounts of data?
Fortunately, those who have come up with the technologies to mitigate these storage concerns have also come up with a way to derive value from what many see as a burden. Big Data Analytics shows how you can leverage big data into a key component in your business's growth strategy.
An essential read for CTOs, CIOs, CFOs, and those looking to leverage Big Data solutions.
Big Data Analytics is now available for purchase online and at retailers nationwide in both print and all e-book formats. For a list of retailers, visit http://www.wiley.com/buy/9781118147597.