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by Pam Baker
Data Divination: Big Data Strategies
Title Page
Copyright Page
Dedication
Acknowledgments
About the Authors
Contents
Introduction
Chapter 1 What Is Big Data, Really?
Technically Speaking
Why Data Size Doesn’t Matter
What Big Data Typically Means to Executives
Big Data Positioned in Executive Speak
Summary
Chapter 2 How to Formulate a Winning Big Data Strategy
The Head Eats the Tail
How to End the “Who’s on First” Conundrum
Next Step: Embracing Ignorance
Where to Start
Identifying Targets and Aiming Your Sights
How to Get Best Practices and Old Mindsets Out of Your Way
Answer the Questions No One Has Asked
Cross-Pollinate the Interpretative Team
Start Small and Build Up and Out
Prototypes and Iterations Strategies
A Word About Adding Predictive Analytics to Your Data Strategy
Democratize Data but Expect Few to Use It (for Now)
Your Strategy Is a Living Document; Nourish It Accordingly
Summary
Chapter 3 How to Ask the“Right” Questions of Big Data
Collaborate on the Questions
The Magic 8 Ball Effect
Translating Human Questions to Software Math
Checklist for Forming the “Right” Questions
Summary
Chapter 4 How to Pick the“Right” Data Sources
You Need More Data Sources (Variety), Not Just More Data (Volume)
Why Your Own Data Isn’t Enough and Will Never Be Enough, No Matter How Large It Grows
Data Hoarding versus Catch and Release
The Mysterious Case of the Diaper-Buying Dog-Owner
The Value in Upsizing Transactional Data
The Limits to Social Media Analysis
The Monetary Value of Data Bought and Sold
Even Hackers Are Having Trouble Making Money on Data
Evaluating the Source
Outdated Models Invite Disruptors
What to Look for When Buying Data
Identifying What Outside Data You Need
A Word About Structured vs. Unstructured Data
Preventing Human Bias in Data Selection
The Danger of Data Silos
Steps to Take to Ensure You’re Using All the Data Sources You Need
Summary
Chapter 5 Why the Answer to Your Big Data Question Resembles a Rubik’s Cube
What Is Actionable Data Anyway?
The Difference Among Descriptive, Predictive, and Prescriptive Analytics
Types of Questions That Get Straight Answers
When Questions Lead to More Questions
Types of Questions That Require Interpretation—The Rubik’s Cube
Summary
Chapter 6 The Role of Real-Time Analytics in Rolling Your Strategy
Examining Real-Time Delusions and Time Capsules
Using Static versus Rolling Strategies
A Word About Change Management in Moving to a Rolling Strategy
Your Choices in Analytics
Using Data from Human Experts’ Brains to Speed Analytics
When Real-Time Is Too Late, Then What?
Summary
Chapter 7 The Big Data Value Proposition and Monetization
Determining ROI in Uncharted Territory
Funny Money and Fuzzy ROI
The Confusion in Cost
Why Cost Isn’t an Issue
Putting the Project Before the Business Case
Calculating Actual Cost
Where Value Actually Resides
Formulas for Calculating Project Returns
The Big Question: Should You Sell Your Data?
Summary
Chapter 8 Rise of the Collaborative Economy and Ways to Profit from It
Data Is Knowledge and an Asset
Big Data’s Biggest Impact: Model Shattering
Examples of New Models Emerging in the New Collaborative Economy
Agile Is Out, Fluid Is In
Using Big Data to Strategize New Models
Summary
Chapter 9 The Privacy Conundrum
The Day the Whistle Blew and Killed the Myth of Individual Privacy
The Four Big Shifts in Data Collection
The Business Question You Must Ask
Who Really Owns the Data?
The Role of Existing Laws and Actions in Setting Precedent
The Fallacies of Consent
Values in Personal versus Pooled Data
The Fallacy in Anonymizing Data
Balancing Individual Privacy with Individual Benefit
When Data Collection Could Make You or Your Company Liable
The Business Value of Transparency
The One Truth That Data Practitioners Must Never Forget
Summary
Chapter 10 Use Cases in the Department of Defense and Intelligence Community
Situational Awareness and Visualization
Information Correlation for Problem Solving (the “Connect the Dots” Problem)
Information Search and Discovery in Overwhelming Amounts of Data (the “Needle in Haystack” Problem)
Enterprise Cyber Security Data Management
Logistical Information, Including Asset Catalogs Across Extensive/Dynamic Enterprises
Enhanced Healthcare
Open Source Information
In-Memory Data Modernization
The Enterprise Data Hub
Big Data Use Cases in Weaponry and War
Summary
Chapter 11 Use Cases in Governments
Effects of Big Data Trends on Governmental Data
United Nations Global Pulse Use Cases
Federal Government (Non-DoD or IC) Use Cases
State Government Use Cases
Local Government Use Cases
Law Enforcement Use Cases
Summary
Chapter 12 Use Cases in Security
Everything Is on the Internet
Data as Friend and Foe
Use Cases in Antivirus/Malware Efforts
How Target Got Hit in the Bull’s Eye
Where Virtual and Real Worlds Collide
Machine Data Mayhem
Current and Future Use of Analytics in Security
Summary
Chapter 13 Use Cases in Healthcare
Solving the Antibiotics Crisis
Using Big Data to Cure Diseases
From Google to the CDC
The Biohacker Side of the Equation
EHRs, EMRs, and Big Data
Medicare Data Goes Public
Summary
Chapter 14 Use Cases in Small Businesses and Farms
Big Data Applies to Small Business
The Line Between Hype and Real-World Limitations
Picking the Right Tool for the Job
Examples of External Data Sources You Might Want to Use
A Word of Caution to Farmers on Pooling or Sharing Data
Money, Money, Money: How Big Data Is Broadening Your Borrowing Power
Summary
Chapter 15 Use Cases in Transportation
Revving Up Data in a Race for Money
Connected Vehicles: They’re Probably Not What You Think They Are
Data and the Driverless Car
Connected Infrastructure
Car Insurance Branded Data Collection Devices
Unexpected Data Liabilities for the Sector
Summary
Chapter 16 Use Cases in Energy
The Data on Energy Myths and Assumptions
EIA Energy Data Repository
EIA Energy Data Table Browsers
Smart Meter Data Is MIA
The EIA’s API and Data Sets
International Implications and Cooperation
Public-Private Collaborative Energy Data Efforts
Utility Use Cases
Summary
Chapter 17 Use Cases in Retail
Old Tactics in a Big Data Re-Run
Why Retail Has Struggled with Big Data
Ways Big Data Can Help Retail
Predicting the Future of Retail
Summary
Chapter 18 Use Cases in Banking and Financial Services
Defining the Problem
Use Cases in Banks and Lending Institutions
How Big Data Fuels New Competitors in the Money-Lending Space
The New Breed of Alternative Lenders
Retailers Take on Banks; Credit Card Brands Circumvent Banks
The Credit Bureau Data Problem
A Word About Insurance Companies
Summary
Chapter 19 Use Cases in Manufacturing
Economic Conditions and Opportunities Ahead
Crossroads in Manufacturing
At the Intersection of 3D Printing and Big Data
How 3D Printing Is Changing Manufacturing and Disrupting Its Customers
The Shift to Additive Manufacturing Will Be Massive and Across All Sectors
How Personalized Manufacturing Will Change Everything and Create Even More Big Data
New Data Sources Springing from Inside Manufacturing
Use Cases for this Sector
Summary
Chapter 20 Empowering the Workforce
Democratizing Data
Four Steps Forward
Four More Steps Forward
Summary
Chapter 21 Executive Summary
What Is Big Data Really?
How to Formulate a Winning Big Data Strategy
How to Ask the “Right” Questions of Big Data
How to Pick the “Right” Data Sources
Why the Answer to Your Big Data Question Resembles a Rubik’s Cube
The Role of Real-Time Analytics in Rolling Your Strategy
The Big Data Value Proposition and Monetization
Rise of the Collaborative Economy and Ways to Profit from It
The Privacy Conundrum
Use Cases in Governments
Use Cases in the Department of Defense and Intelligence Community
Use Cases in Security
Use Cases in Healthcare
Use Cases in Small Businesses and Farms
Use Cases in Energy
Use Cases in Transportation
Use Cases in Retail
Use Cases in Banking and Financial Services
Use Cases in Manufacturing
Empowering the Workforce
Index
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Copyright Page
D
ATA
D
IVINATION
: B
IG
D
ATA
S
TRATEGIES
P
AM
B
AKER
Cengage Learning PTR
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