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Book Description

Learn how big data and other sources of information can be transformed into valuable knowledge - knowledge that can create incredible competitive advantage to propel a business toward market leadership.

Learn through examples and experience exactly how to pick projects and build analytics teams that deliver results. Know the ethical and privacy issues, and apply the three-part litmus test of context, permission, and accuracy.

Without a doubt, data and analytics are the new source of competitive advantage, but how do executives go from hype to action? That's the objective of this book - to assist executives in making the right investments in the right place and at the right time in order to reap the full benefits of data analytics.

We are moving into an era where information is potentially more valuable than tangible things or services. Organizations who connect information with their product will have a huge advantage, and conversely organizations that miss this transformation will find themselves increasingly un-competitive. No longer just something for the Information Technologists or Data Scientists to deal with, everyone who makes things or serves customers in some way needs to understand how people interact with their product or service in a very granular way. This book will help people in business and government understand the power of data analytics technology and how some of the tools available can be applied to a wide range of applications.
John Swainson, former President, Dell Software Group

John and Shawn bring decades of hands on experience helping clients understand where and how data and analytics can deliver business value and market differentiation. The authors do not get bogged down in the technology tail-chase, but instead provides clear and actionable guidance on how organizations need to embrace a 'business first' approach when considering how to exploit the business potential of big data. Like I ask my clients, "How effective is your organization at leveraging data and analytics to power your business?" It's a question this book will help you to address.
Bill Schmarzo, CTO Big Data, Dell Technologies Services

One could argue - and probably easily win the argument - that there has been more change in analytics over the past ten years than at any time in the history of the world. For that reason alone, a book like this one that provides a clear-eyed assessment of the state of the art in analytics is enormously valuable.
Thomas H. Davenport

Table of Contents

  1. Foreword by Tom Davenport
  2. CHAPTER 1 Competitive Advantage Stemming from Analytics
    1. New opportunities
    2. A brief history of analytics
    3. Data gets big
      1. Does size matter?
    4. The challenge of data management
    5. “Analytics” defined
    6. An inflection point: three major trends
      1. The rise of “citizen data scientists”
      2. The availability of easy-to-use, cheaper technology
      3. The abundance of data
    7. Challenges ahead
    8. Conclusion
  3. CHAPTER 2 Understanding Advanced Analytics
    1. Advanced analytics: then and now
    2. The power of agile methodologies
    3. Advanced analytics today
    4. The process of advanced analytics
    5. The future of advanced analytics
    6. Conclusion
  4. CHAPTER 3 The Age of the Algorithm Economy
    1. Beyond the digital economy
    2. It’s not just about the data
    3. Creating products using data and insights
    4. Reinvention through algorithms
    5. Don’t reinvent the wheel – borrow it
    6. Algorithms gone wild
    7. Conclusion
  5. CHAPTER 4 The Modern Data Ecosystem
    1. 1. Maturing users
    2. 2. New technologies
    3. 3. Decreasing cost barriers
    4. 4. Abundant data
    5. Ecosystem challenges
    6. Conclusion
  6. CHAPTER 5 Analytics Takes a Village: Building and Enabling the Right Team
    1. Analytic Centers of Excellence (COEs)
    2. The Chief Analytics Officer
    3. COE organizational models
    4. The COE staff
    5. Different data scientist roles
    6. Citizen data scientists
    7. The COE in action
    8. Conclusion
  7. CHAPTER 6 Getting Started
    1. Build or buy?
    2. Crucial user interfaces
    3. The monetization of data
    4. Consider. Think. Decide.
    5. A hypothetical project
    6. Conclusion
  8. CHAPTER 7 Operational Analytics: Advanced Analytics in the Modern Corporation
    1. Marketing/Sales
    2. Financial services
    3. Logistics/Supply chain
    4. Manufacturing
      1. Process manufacturing
      2. Discrete manufacturing
    5. Fraud and theft
    6. Conclusion
  9. CHAPTER 8 Analytics Everywhere, All the Time
    1. Agile and ubiquitous
      1. Real time
      2. Speed, measured in hours
      3. Model portability
      4. Models everywhere
      5. Moving models to the data
    2. Limited only by the imagination
      1. ADP
      2. Whirlpool
      3. Georgia Aquarium
      4. NASCAR
    3. Conclusion
  10. Chapter 9 Innovative or Icky?
    1. Pushing the innovation envelope
    2. Context, permission, and accuracy
    3. Target’s targeting of pregnant women
    4. About those “free” drinks
    5. That feeling of being watched
    6. Finding the right path
    7. Conclusion
  11. CHAPTER 10 What Now?
    1. Reason for fear?
    2. A tool for augmenting human capacities
    3. A new era
    4. Conclusion