Search icon CANCEL
Subscription
0
Cart icon
Cart
Close icon
You have no products in your basket yet
Save more on your purchases!
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Introduction to R for Business Intelligence

You're reading from  Introduction to R for Business Intelligence

Product type Book
Published in Aug 2016
Publisher Packt
ISBN-13 9781785280252
Pages 228 pages
Edition 1st Edition
Languages
Author (1):
Jay Gendron Jay Gendron
Profile icon Jay Gendron
Toc

Table of Contents (19) Chapters close

Introduction to R for Business Intelligence
Credits
About the Author
Acknowledgement
About the Reviewers
www.PacktPub.com
Preface
1. Extract, Transform, and Load 2. Data Cleaning 3. Exploratory Data Analysis 4. Linear Regression for Business 5. Data Mining with Cluster Analysis 6. Time Series Analysis 7. Visualizing the Datas Story 8. Web Dashboards with Shiny References
Other Helpful R Functions R Packages Used in the Book
R Code for Supporting Market Segment Business Case Calculations

Acknowledgement

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 https://github.com/ReportMort.

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 https://kannandreams.wordpress.com/ 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.

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime