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Data Divination: Big Data Strategies

Author Pam Baker
Release Date: 2014/08/01
ISBN: 9781305115088
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Book Description

Our world is being transformed by big data. The growth of the Internet and the rapid expansion of mobile communications and related technologies have created a massive flow of data-both structured and unstructured. The availability and use of that data has enormous implications for businesses and for the wider society. Used effectively, big data can drive businesses in the direction of more accurate analyses of vital information. More accurate analyses can lead to more confident decision making--and eventually to greater operational efficiencies, cost reductions, reduced risk, speedier innovations, and increased and new revenue. This book offers detailed instruction in big-data strategy development and implementation, supported by numerous real-world business cases in ten distinct industries. You will learn what big data is and how to wield it-from calculating ROI and making a business case to developing overall and project-specific strategies that actually work. Each chapter answers key questions and will give you the skills you need to make your big data projects succeed. Put big data to work for you and your company today, with DATA DIVINATION: BIG DATA STRATEGIES

Table of Contents

  1. Title Page
  2. Copyright Page
  3. Dedication
  4. Acknowledgments
  5. About the Authors
  6. Contents
  7. Introduction
  8. Chapter 1 What Is Big Data, Really?
    1. Technically Speaking
    2. Why Data Size Doesn’t Matter
    3. What Big Data Typically Means to Executives
    4. Big Data Positioned in Executive Speak
    5. Summary
  9. Chapter 2 How to Formulate a Winning Big Data Strategy
    1. The Head Eats the Tail
    2. How to End the “Who’s on First” Conundrum
    3. Next Step: Embracing Ignorance
    4. Where to Start
    5. Identifying Targets and Aiming Your Sights
    6. How to Get Best Practices and Old Mindsets Out of Your Way
    7. Answer the Questions No One Has Asked
    8. Cross-Pollinate the Interpretative Team
    9. Start Small and Build Up and Out
    10. Prototypes and Iterations Strategies
    11. A Word About Adding Predictive Analytics to Your Data Strategy
    12. Democratize Data but Expect Few to Use It (for Now)
    13. Your Strategy Is a Living Document; Nourish It Accordingly
    14. Summary
  10. Chapter 3 How to Ask the“Right” Questions of Big Data
    1. Collaborate on the Questions
    2. The Magic 8 Ball Effect
    3. Translating Human Questions to Software Math
    4. Checklist for Forming the “Right” Questions
    5. Summary
  11. Chapter 4 How to Pick the“Right” Data Sources
    1. You Need More Data Sources (Variety), Not Just More Data (Volume)
    2. Why Your Own Data Isn’t Enough and Will Never Be Enough, No Matter How Large It Grows
    3. Data Hoarding versus Catch and Release
    4. The Mysterious Case of the Diaper-Buying Dog-Owner
    5. The Value in Upsizing Transactional Data
    6. The Limits to Social Media Analysis
    7. The Monetary Value of Data Bought and Sold
    8. Even Hackers Are Having Trouble Making Money on Data
    9. Evaluating the Source
    10. Outdated Models Invite Disruptors
    11. What to Look for When Buying Data
    12. Identifying What Outside Data You Need
    13. A Word About Structured vs. Unstructured Data
    14. Preventing Human Bias in Data Selection
    15. The Danger of Data Silos
    16. Steps to Take to Ensure You’re Using All the Data Sources You Need
    17. Summary
  12. Chapter 5 Why the Answer to Your Big Data Question Resembles a Rubik’s Cube
    1. What Is Actionable Data Anyway?
    2. The Difference Among Descriptive, Predictive, and Prescriptive Analytics
    3. Types of Questions That Get Straight Answers
    4. When Questions Lead to More Questions
    5. Types of Questions That Require Interpretation—The Rubik’s Cube
    6. Summary
  13. Chapter 6 The Role of Real-Time Analytics in Rolling Your Strategy
    1. Examining Real-Time Delusions and Time Capsules
    2. Using Static versus Rolling Strategies
    3. A Word About Change Management in Moving to a Rolling Strategy
    4. Your Choices in Analytics
    5. Using Data from Human Experts’ Brains to Speed Analytics
    6. When Real-Time Is Too Late, Then What?
    7. Summary
  14. Chapter 7 The Big Data Value Proposition and Monetization
    1. Determining ROI in Uncharted Territory
    2. Funny Money and Fuzzy ROI
    3. The Confusion in Cost
    4. Why Cost Isn’t an Issue
    5. Putting the Project Before the Business Case
    6. Calculating Actual Cost
    7. Where Value Actually Resides
    8. Formulas for Calculating Project Returns
    9. The Big Question: Should You Sell Your Data?
    10. Summary
  15. Chapter 8 Rise of the Collaborative Economy and Ways to Profit from It
    1. Data Is Knowledge and an Asset
    2. Big Data’s Biggest Impact: Model Shattering
    3. Examples of New Models Emerging in the New Collaborative Economy
    4. Agile Is Out, Fluid Is In
    5. Using Big Data to Strategize New Models
    6. Summary
  16. Chapter 9 The Privacy Conundrum
    1. The Day the Whistle Blew and Killed the Myth of Individual Privacy
    2. The Four Big Shifts in Data Collection
    3. The Business Question You Must Ask
    4. Who Really Owns the Data?
    5. The Role of Existing Laws and Actions in Setting Precedent
    6. The Fallacies of Consent
    7. Values in Personal versus Pooled Data
    8. The Fallacy in Anonymizing Data
    9. Balancing Individual Privacy with Individual Benefit
    10. When Data Collection Could Make You or Your Company Liable
    11. The Business Value of Transparency
    12. The One Truth That Data Practitioners Must Never Forget
    13. Summary
  17. Chapter 10 Use Cases in the Department of Defense and Intelligence Community
    1. Situational Awareness and Visualization
    2. Information Correlation for Problem Solving (the “Connect the Dots” Problem)
    3. Information Search and Discovery in Overwhelming Amounts of Data (the “Needle in Haystack” Problem)
    4. Enterprise Cyber Security Data Management
    5. Logistical Information, Including Asset Catalogs Across Extensive/Dynamic Enterprises
    6. Enhanced Healthcare
    7. Open Source Information
    8. In-Memory Data Modernization
    9. The Enterprise Data Hub
    10. Big Data Use Cases in Weaponry and War
    11. Summary
  18. Chapter 11 Use Cases in Governments
    1. Effects of Big Data Trends on Governmental Data
    2. United Nations Global Pulse Use Cases
    3. Federal Government (Non-DoD or IC) Use Cases
    4. State Government Use Cases
    5. Local Government Use Cases
    6. Law Enforcement Use Cases
    7. Summary
  19. Chapter 12 Use Cases in Security
    1. Everything Is on the Internet
    2. Data as Friend and Foe
    3. Use Cases in Antivirus/Malware Efforts
    4. How Target Got Hit in the Bull’s Eye
    5. Where Virtual and Real Worlds Collide
    6. Machine Data Mayhem
    7. Current and Future Use of Analytics in Security
    8. Summary
  20. Chapter 13 Use Cases in Healthcare
    1. Solving the Antibiotics Crisis
    2. Using Big Data to Cure Diseases
    3. From Google to the CDC
    4. The Biohacker Side of the Equation
    5. EHRs, EMRs, and Big Data
    6. Medicare Data Goes Public
    7. Summary
  21. Chapter 14 Use Cases in Small Businesses and Farms
    1. Big Data Applies to Small Business
    2. The Line Between Hype and Real-World Limitations
    3. Picking the Right Tool for the Job
    4. Examples of External Data Sources You Might Want to Use
    5. A Word of Caution to Farmers on Pooling or Sharing Data
    6. Money, Money, Money: How Big Data Is Broadening Your Borrowing Power
    7. Summary
  22. Chapter 15 Use Cases in Transportation
    1. Revving Up Data in a Race for Money
    2. Connected Vehicles: They’re Probably Not What You Think They Are
    3. Data and the Driverless Car
    4. Connected Infrastructure
    5. Car Insurance Branded Data Collection Devices
    6. Unexpected Data Liabilities for the Sector
    7. Summary
  23. Chapter 16 Use Cases in Energy
    1. The Data on Energy Myths and Assumptions
    2. EIA Energy Data Repository
    3. EIA Energy Data Table Browsers
    4. Smart Meter Data Is MIA
    5. The EIA’s API and Data Sets
    6. International Implications and Cooperation
    7. Public-Private Collaborative Energy Data Efforts
    8. Utility Use Cases
    9. Summary
  24. Chapter 17 Use Cases in Retail
    1. Old Tactics in a Big Data Re-Run
    2. Why Retail Has Struggled with Big Data
    3. Ways Big Data Can Help Retail
    4. Predicting the Future of Retail
    5. Summary
  25. Chapter 18 Use Cases in Banking and Financial Services
    1. Defining the Problem
    2. Use Cases in Banks and Lending Institutions
    3. How Big Data Fuels New Competitors in the Money-Lending Space
    4. The New Breed of Alternative Lenders
    5. Retailers Take on Banks; Credit Card Brands Circumvent Banks
    6. The Credit Bureau Data Problem
    7. A Word About Insurance Companies
    8. Summary
  26. Chapter 19 Use Cases in Manufacturing
    1. Economic Conditions and Opportunities Ahead
    2. Crossroads in Manufacturing
    3. At the Intersection of 3D Printing and Big Data
    4. How 3D Printing Is Changing Manufacturing and Disrupting Its Customers
    5. The Shift to Additive Manufacturing Will Be Massive and Across All Sectors
    6. How Personalized Manufacturing Will Change Everything and Create Even More Big Data
    7. New Data Sources Springing from Inside Manufacturing
    8. Use Cases for this Sector
    9. Summary
  27. Chapter 20 Empowering the Workforce
    1. Democratizing Data
    2. Four Steps Forward
    3. Four More Steps Forward
    4. Summary
  28. Chapter 21 Executive Summary
    1. What Is Big Data Really?
    2. How to Formulate a Winning Big Data Strategy
    3. How to Ask the “Right” Questions of Big Data
    4. How to Pick the “Right” Data Sources
    5. Why the Answer to Your Big Data Question Resembles a Rubik’s Cube
    6. The Role of Real-Time Analytics in Rolling Your Strategy
    7. The Big Data Value Proposition and Monetization
    8. Rise of the Collaborative Economy and Ways to Profit from It
    9. The Privacy Conundrum
    10. Use Cases in Governments
    11. Use Cases in the Department of Defense and Intelligence Community
    12. Use Cases in Security
    13. Use Cases in Healthcare
    14. Use Cases in Small Businesses and Farms
      1. Use Cases in Energy
      2. Use Cases in Transportation
      3. Use Cases in Retail
      4. Use Cases in Banking and Financial Services
      5. Use Cases in Manufacturing
    15. Empowering the Workforce
  29. Index
3.145.95.244