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.

Praise for Analytics: The Agile Way

"As analytics moves from an IT reporting exercise to a mission critical business-led discipline, collaboration, expediency, and flexibility are more important than ever. Information is no longer an asset to be trifled with, but rather one that organizations must harness aggressively. To date, I have seen scant attempts at Agile analytics, but this book will most certainly launch a thousand more. It is a must-read for any analytics leader, and a must-do for any analytics professional."
Douglas Laney, VP and Distinguished Analyst, Gartner

"Analytics: The Agile Way makes accessible two of today's key themes in modern business: data and how we get work done. A great book for analytics, but also a great book for management and leadership. Given that we are all responsible for our own education, perhaps all business books should now be written as this one is: perfect for a formal class but also for lifelong learning."
Terri Griffith, Associate Dean & Professor at Santa Clara University's Leavey School of Business and author of the award-winning book The Plugged-In Manager

"Phil Simon adroitly shows the potential of combining Agile thinking and methods with data analytics to provide powerful, distinct competitive advantages to organizations. As Simon demonstrates clearly through multiple real-life examples, Agile analytics can enable organizations to create lasting value from their Big Data efforts without ignoring the privacy and security issues those efforts frequently create."
Robert N. Charette, President, ITABHI Corporation

"A thoroughly enjoyable guide to the critical importance of analytics and Big Data. Simon wisely counsels that no one method works for all companies. The key is to be flexible and nimble and follow the guidelines he explains so clearly and convincingly."
Gary N. Smith, Fletcher Jones Professor of Economics at Pomona College and author of Money Machine: The Surprisingly Simple Power of Value Investing

Inhalt

Preface: The Power of Dynamic Data xvii

List of Figures and Tables xxvii

Introduction: It Didn't Used to Be This Way 1

A Little History Lesson 2

Analytics and the Need for Speed 5

Book Scope, Approach, and Style 9

Intended Audience 12

Plan of Attack 13

Next 14

Notes 14

Part One Background and Trends 17

Chapter 1 Signs of the Times: Why Data and Analytics Are Dominating Our World 19

The Moneyball Effect 20

Digitization and the Great Unbundling 22

Amazon Web Services and Cloud Computing 24

Not Your Father's Data Storage 26

Moore's Law 28

The Smartphone Revolution 28

The Democratization of Data 29

The Primacy of Privacy 29

The Internet of Things 31

The Rise of the Data-Savvy Employee 31

The Burgeoning Importance of Data Analytics 32

Data-Related Challenges 40

Companies Left Behind 41

The Growth of Analytics Programs 42

Next 43

Notes 43

Chapter 2 The Fundamentals of Contemporary Data: A Primer on What It Is, Why It Matters, and How to Get It 45

Types of Data 46

Getting the Data 52

Data in Motion 61

Next 63

Notes 63

Chapter 3 The Fundamentals of Analytics: Peeling Back the Onion 65

Defining Analytics 66

Types of Analytics 69

Streaming Data Revisited 72

A Final Word on Analytics 74

Next 75

Notes 75

Part Two Agile Methods and Analytics 77

Chapter 4 A Better Way to Work: The Benefits and Core Values of Agile Development 79

The Case against Traditional Analytics Projects 80

Proving the Superiority of Agile Methods 82

The Case for Guidelines over Rules 84

Next 88

Notes 88

Chapter 5 Introducing Scrum: Looking at One of Today's Most Popular Agile Methods 89

A Very Brief History 90

Scrum Teams 91

User Stories 94

Backlogs 97

Sprints and Meetings 98

Releases 101

Estimation Techniques 102

Other Scrum Artifacts, Tools, and Concepts 109

Next 112

Chapter 6 A Framework for Agile Analytics: A Simple Model for Gathering Insights 113

Perform Business Discovery 115

Perform Data Discovery 117

Prepare the Data 118

Model the Data 120

Score and Deploy 127

Evaluate and Improve 128

Next 130

Notes 130

Part Three Analytics in Action 131

Chapter 7 University Tutoring Center: An In-Depth Case Study on Agile Analytics 133

The UTC and Project Background 134

Project Goals and Kickoff 136

Iteration One 139

Iteration Two 140

Iteration Three 145

Iteration Four 146

Results 147

Lessons 148

Next 148

Chapter 8 People Analytics at Google/Alphabet: Not Your Father's HR Department 149

The Value of Business Experiments 150

PiLab's Adventures in Analytics 151

A Better Approach to Hiring 153

Staffing 156

The Value of Perks 158

Results and Lessons 162

Next 162

Notes 163

Chapter 9 The Anti-Google: Beneke Pharmaceuticals 165

Project Background 166

Business and Data Discovery 167

The Friction Begins 168

Astonishing Results 169

Developing Options 171

The Grand Finale 172

Results and Lessons 173

Next 174

Chapter 10 Ice Station Zebra Medical: How Agile Methods Solved a Messy Health-Care Data P...