Growing Business Intelligence

How do we enable our organizations to enjoy the often significant benefits of BI and analytics, while at the same time minimizing the cost and risk of failure? In this book, I am not going to try to be prescriptive; I won’t tell you exactly how to build your BI environment. Instead, I am going to focus on a few core principles that will enable you to navigate the rocky shoals of BI architecture and arrive at a destination best suited for your particular organization. 


Some of these core principles include:

- Have an overarching strategy, plan, and roadmap

- Recognize and leverage your existing technology investments

- Support both data discovery and data reuse

- Keep data in motion, not at rest

- Separate information delivery from data storage

- Emphasize data transparency over data quality

- Take an agile approach to BI development.


This book will show you how to successfully navigate both the jungle of BI technology and the minefield of human nature. It will show you how to create a BI architecture and strategy that addresses the needs of all organizational stakeholders. It will show you how to maximize the value of your BI investments. It will show you how to manage the risk of disruptive technology. And it will show you how to use agile methodologies to deliver on the promise of BI and analytics quickly, succinctly, and iteratively.


This book is about many things. But principally, it’s about success. The goal of any enterprise initiative is to succeed and to derive benefit—benefit that all stakeholders can share in. I want you to be successful. I want your organization to be successful. This book will show you how.

This book is for anyone who is currently or will someday be working on a BI, analytics, or Big Data project, and for organizations that want to get the maximum amount of value from both their data and their BI technology investment. This includes all stakeholders in the BI effort—not just the data people or the IT people, but also the business stakeholders who have the responsibility for the definition and use of data.