Book description

For years, organizations have struggled to make sense out of their data. IT projects designed to provide employees with dashboards, KPIs, and business-intelligence tools often take a year or more to reach the finish line...if they get there at all.

This has always been a problem. Today, though, it's downright unacceptable. The world changes faster than ever. Speed has never been more important. By adhering to antiquated methods, firms lose the ability to see nascent trends—and act upon them until it's too late.

But what if the process of turning raw data into meaningful insights didn't have to be so painful, time-consuming, and frustrating?

What if there were a better way to do analytics?

Fortunately, you're in luck...

Analytics: The Agile Way is the eighth book from award-winning author and Arizona State University professor Phil Simon.

Analytics: The Agile Way demonstrates how progressive organizations such as Google, Nextdoor, and others approach analytics in a fundamentally different way. They are applying the same Agile techniques that software developers have employed for years. They have replaced large batches in favor of smaller ones...and their results will astonish you.

Through a series of case studies and examples, Analytics: The Agile Way demonstrates the benefits of this new analytics mind-set: superior access to information, quicker insights, and the ability to spot trends far ahead of your competitors.

Table of contents

  1. Preface: The Power of Dynamic Data
  2. Introduction It Didn’t Used to Be This Way
    1. A Little History Lesson
    2. Analytics and the Need for Speed
    3. Book Scope, Approach, and Style
    4. Intended Audience
    5. Plan of Attack
    6. Next
    7. Notes
  3. Part One Background and Trends
    1. Chapter 1 Signs of the Times Why Data and Analytics Are Dominating Our World
      1. The Moneyball Effect
      2. Digitization and the Great Unbundling
      3. Amazon Web Services and Cloud Computing
      4. Not Your Father’s Data Storage
      5. Moore’s Law
      6. The Smartphone Revolution
      7. The Democratization of Data
      8. The Primacy of Privacy
      9. The Internet of Things
      10. The Rise of the Data-Savvy Employee
      11. The Burgeoning Importance of Data Analytics
      12. Data-Related Challenges
      13. Companies Left Behind
      14. The Growth of Analytics Programs
      15. Next
      16. Notes
    2. Chapter 2 The Fundamentals of Contemporary Data A Primer on What It Is, Why It Matters, and How to Get It
      1. Types of Data
      2. Getting the Data
      3. Data in Motion
      4. Next
      5. Notes
    3. Chapter 3 The Fundamentals of Analytics Peeling Back the Onion
      1. Defining Analytics
      2. Types of Analytics
      3. Streaming Data Revisited
      4. A Final Word on Analytics
      5. Next
      6. Notes
  4. Part Two Agile Methods and Analytics
    1. Chapter 4 A Better Way to Work The Benefits and Core Values of Agile Development
      1. The Case against Traditional Analytics Projects
      2. Proving the Superiority of Agile Methods
      3. The Case for Guidelines over Rules
      4. Next
      5. Notes
    2. Chapter 5 Introducing Scrum Looking at One of Today’s Most Popular Agile Methods
      1. A Very Brief History
      2. Scrum Teams
      3. User Stories
      4. Backlogs
      5. Sprints and Meetings
      6. Releases
      7. Estimation Techniques
      8. Other Scrum Artifacts, Tools, and Concepts
      9. Next
      10. Notes
    3. Chapter 6 A Framework for Agile Analytics A Simple Model for Gathering Insights
      1. Perform Business Discovery
      2. Perform Data Discovery
      3. Prepare the Data
      4. Model the Data
      5. Score and Deploy
      6. Evaluate and Improve
      7. Next
      8. Notes
  5. Part Three Analytics in Action
    1. Chapter 7 University Tutoring Center An In-Depth Case Study on Agile Analytics
      1. The UTC and Project Background
      2. Project Goals and Kickoff
      3. Iteration One
      4. Iteration Two
      5. Iteration Three
      6. Iteration Four
      7. Results
      8. Lessons
      9. Next
      10. Notes
    2. Chapter 8 People Analytics at Google/Alphabet Not Your Father’s HR Department
      1. The Value of Business Experiments
      2. PiLab’s Adventures in Analytics
      3. A Better Approach to Hiring
      4. Staffing
      5. The Value of Perks
      6. Results and Lessons
      7. Next
      8. Notes
    3. Chapter 9 The Anti-Google Beneke Pharmaceuticals
      1. Project Background
      2. Business and Data Discovery
      3. The Friction Begins
      4. Astonishing Results
      5. Developing Options
      6. The Grand Finale
      7. Results and Lessons
      8. Next
      9. Notes
    4. Chapter 10 Ice Station Zebra Medical How Agile Methods Solved a Messy Health-Care Data Problem
      1. Paying Nurses
      2. Enter the Consultant
      3. User Stories
      4. Agile: The Better Way
      5. Results
      6. Lessons
      7. Next
      8. Notes
    5. Chapter 11 Racial Profiling at Nextdoor Using Data to Build a Better App and Combat a PR Disaster
      1. Unintended but Familiar Consequences
      2. Evaluating the Problem
      3. Results and Lessons
      4. Next
      5. Notes
  6. Part Four Making the Most Out of Agile Analytics
    1. Chapter 12 The Benefits of Agile Analytics The Upsides of Small Batches
      1. Life at IAC
      2. Life at RDC
      3. Comparing the Two
      4. Next
      5. Notes
    2. Chapter 13 No Free Lunch The Impediments to—and Limitations of—Agile Analytics
      1. People Issues
      2. Data Issues
      3. The Limitations of Agile Analytics
      4. Next
      5. Notes
    3. Chapter 14 The Importance of Designing for Data Lessons from the Upstarts
      1. The Genes of Music
      2. The Tension between Data and Design
      3. Next
      4. Notes
  7. Part Five Conclusions and Next Steps
    1. Chapter 15 What Now? A Look Forward
      1. A Tale of Two Retailers
      2. The Blurry Futures of Data, Analytics, and Related Issues
      3. Final Thoughts and Next Steps
      4. Notes
  8. Afterword
  9. Acknowledgments
  10. Selected Bibliography
    1. Books
    2. Articles and Essays
  11. About the Author
  12. Index
  13. EULA

Product information

  • Title: Analytics
  • Author(s): Phil Simon
  • Release date: July 2017
  • Publisher(s): Wiley
  • ISBN: 9781119423478