The Analytics Lifecycle Toolkit

Preface

The modern enterprise is often characterized as “data rich, but information poor.” This challenge is exacerbated by the pure volume and variety of data generated at the point of interaction (e.g., customers, patients, suppliers) and careening outward. Whether you are preparing, analyzing, presenting, or consuming data, having a strong foundation in data and analytics is paramount for conveying ideas effectively.

In this book, I translate the world of big data, data science, and analytics into a practical, comprehensive guide where you can explore the art and science of analytics best practices through a proven framework for managing analytics teams and processes.

The focus of the book is on creating effective and efficient analytics organizations and processes in order to strengthen the role of data and analytics in producing organizational success.

When I started thinking about writing about this specific topic, it was primarily in response to the lack of information about “the people and process” side of analytics. That is, for over a decade, authors have written about the concept of analytics, its importance in business, and specific implementations of technologies such as Python, R, or SAS, among others. However, those resources generally do not address the tactics of analytics model development or business case development, nor do they address the impact of analytics on operational processes.

The issues that organizations have grappled with over the past 10 years ...