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To Nick and MaryLu, for showing me what it means to be a part of something bigger than yourself.
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 since Tom Davenport and Jeanne Harris published their seminal work Competing on Analytics (Davenport & Harris, 2007) have shifted from “What problems can we solve with analytics?” to “How do we find, nurture, and retain analytics professionals?” This shift from the “what” to the “how” supports the basic premise of this book. I also think the timing is right for the book, as entire industries are transforming themselves with the use of data and analytics. While many organizations have solved the barriers of effectively using analytics in everyday operations as well as strategic decision making, other industries are just now getting on the “analytics bandwagon,” and they see the promise of analytics without a clear roadmap for getting there. For the former, the challenge is one of effectiveness and improved efficiencies. For the latter, the real struggle can often be with creating an organizational culture—or mindset—for analytics, justifying the development of an analytics capability, and organizing for success.
My personal inspiration for this book came from the works of Ralph Kimball. I remember reading his first edition of the Data Warehouse Toolkit (Kimball, 1996) and thinking to myself, “This makes sense.” It was so very different from the conceptual treatments often found in business and technology books, in that Kimball gave us the language, tools, and processes to actually do data warehousing. He provided a solid overview of the areas relevant to someone who was either familiar with or completely new to data warehousing, along with a framework for the data warehousing lifecycle and key process areas. I hope that you will find that The Analytics Lifecycle Toolkit lives up to this inspiration and that it provides a comprehensive and practical guide to the Analytics Lifecycle with focus on creating an effective analytics capability for your organization.
This book differs from other “how-to” books in that it is not designed as a cookbook of analytics models, but rather, is a primer on the best practices and processes used in analytics. It is intended for:
This book is organized in three sections:
In the first chapter, you will see that the language of analytics can be confusing and even down right daunting. Terms like the science of, the discipline of, and the best practice of generally refer to the usual manner in which analytics are conceptualized.
However, terms like method, methodology, or approach typically mean the processes used in common practice.
One of my goals in writing The Analytics Lifecycle Toolkit is to assume nothing and to clarify things along the way. To that end, I will do my best to make analytics accessible by providing explicit examples and using precise language wherever possible.
You've made it this far, so perhaps you agree that this topic is interesting and worth the price of admission. But if you need 10 more reasons, here they are:
This book:
Hopefully, this book will provide some useful guidance for those just starting their analytics journey and some tips for those more experienced. Happy trails!
This work would not have been possible without the support of my colleagues and clients who gave me the space to write. I am especially indebted to Monica Horvath, PhD, for picking up the pieces I dropped along the way. Not only did she provide scrutiny during technical review of this book, but was my sounding board and co-conspirator for the past several years at ThotWave as we helped clients improve the “people and process side of analytics.” Much of the content around organizational design and our analytics competency model was rooted in these efforts.
I am grateful to all of those with whom I have had the pleasure to work during this project. I learn from each of my clients at ThotWave and my professional colleagues throughout the industry as they continue to teach me a great deal about the real-world implications of analytics and the real struggles that organizations have.
I am indebted to those who agreed to review drafts of this book. In particular, I want to thank Anne Milley from JMP Software; Marc Vaglio-Luarin, analytics product manager from Qlik Software; Linda Burtch, founder of Burtch Works; Mark Tabladillo, lead data scientist from Microsoft; Randy Betancourt from Accenture; Robert Gladden, chief analytics officer at Highmark Health; Mary Beth Ainsworth, product marketing at SAS for artificial intelligence and text analytics; and Teddy Benson from the Walt Disney Company. Your contributions to this work made it a better product.
I would especially like to thank my personal copyeditor, MaryLu Giver. Despite the massive amount of red ink, she was encouraging, thorough, and incredibly kind. In addition, thanks goes to the editorial team at Wiley and, in particular, Julie Kerr, who made the process of publishing a book easy and allowed me to focus on the writing.
Nobody has been more important to me in the pursuit of this project than the members of my family. I would like to thank my family, whose love and guidance are with me in whatever I pursue. They are the ultimate role models. Most importantly, I wish to thank my loving and supportive wife, Susan, who makes me a better person, and my daughter and grandson, who give me hope.