Book Image

Introduction to R for Business Intelligence

By : Jay Gendron
Book Image

Introduction to R for Business Intelligence

By: Jay Gendron

Overview of this book

Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance. In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards. After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence.
Table of Contents (19 chapters)
Introduction to R for Business Intelligence
About the Author
About the Reviewers
R Packages Used in the Book
R Code for Supporting Market Segment Business Case Calculations


I am most grateful to God. He has given all of us individual gifts so that we can serve others in this life. I am thankful for the opportunities and abilities that He has bestowed upon me.

I wish to express heartfelt love and gratitude to my wife, Cindy. She is my toughest critic and my greatest coach. She has been with me during every step of this journey. She was there during the toughest of times and celebrated the book's completion. This book would not exist without her loving support. For that, I thank her more than mere words can express.

Thank you to section contributor, Shantanu Saha. He is a talented and energetic data scientist. Shantanu contributed his skills to help author Chapter 7, Visualizing the Data’s Story. He has a great future in this field and I look forward to seeing his work as he continues to analyze and write.

I would like to also thank the author of the BI Tips, Jesse Barboza,who has developed business intelligence systems for over 12 years. One goal of this book was to enhance cross-functional understanding between the analytic and business communities. Jesse created tips for both, R developers new to the business and business analysts new to R.

Finally, I would like to thank the contributing authors, Rick Jones (Chapter 4, Linear Regression for Business) and Steven Mortimer (Chapter 8, Web Dashboards with Shiny). Steven was also a major contributor to Chapter 7, Visualizing the Data’s Story. Their perspectives bring better insights and greater value to the book.  

Contributing Authors:

Rick Jones

I would like to thank Rick Jones for his work in developing the statistical approaches and rigor in Chapter 4, Linear Regression for Business. Rick is a retired United States Navy SEAL officer. While on active duty, he was awarded a subspecialty in information technology management for having spent over six years managing IT research, development, and acquisition programs. He also worked as a computer scientist at the United States Naval Research Laboratory, where he led the development of a wireless network emulator to function as the testbed in a Defense Advanced Research Projects Agency cybersecurity program. After ten years in systems development as a civilian, Rick made a career shift to data analytics, where he has been active in developing a data science community in Norfolk, Virginia.  He currently works as a data science consultant and specializes in machine learning classification problems. He has master's degrees in information systems technology and applied statistics.

Steven Mortimer

Steven Mortimer has provided readers great insights by authoring Chapter 8, Web Dashboards with Shiny. The app design and thought process is immensely useful in a web-based world relying more on data products. Steven is a statistician-turned-data scientist. His passion for helping others make data-driven decisions has led to a variety of projects in the healthcare, higher education, and dot-com industries. The constant in his experiences has been utilizing the R ecosystem of tools, including RStudio, R Markdown, and Shiny. He is an active contributor to a few R packages, acting as a contributor to the RForcecom package and author and creator of the rdfp and roas packages. Steven holds a master's degree in statistics from the University of Virginia. Much of his code is publicly available in his GitHub repositories at

Kannan Kalidasan

Kannan Kalidasan, a data engineer at Expedia Inc., is an autodidact and an open source evangelist.

He has 10 years of work experience in data management, distributed computing, and analytics, contributing as a developer, architect, tech lead, and DBA.

He was one of the technical reviewers for the book R Data Visualization Cookbook published by Packt Publishing.

He, being passionate about technology, had his own tech startup in 2005, when he was pursuing his bachelor of technology (computer science) from Pondicherry University.

He loves to mentor fellow enthusiasts, take long walks alone, write poems in Tamil, paint, and read books. He blogs at and tweets at @kannanpoem.

Big thanks to all those who have been a great support and believed that I could do something substantial in life.