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Introduction to R for Business Intelligence
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Introduction to R for Business Intelligence
Copyright Ā© 2016 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
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First published: August 2016
Production reference: 1230816
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham
B3 2PB, UK.
ISBN 978-1-78528-025-2
www.packtpub.com
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Jay Gendron is an associate data scientist working with Booz Allen Hamilton. He has worked in the fields of machine learning, data analysis, and statistics for over a decade, and believes that good questions and compelling visualization make analytics accessible to decision makers. Jay is a business leader, entrepreneurial employee, artist, and author. He has a B.S.M.E. in mechanical engineering, an M.S. in management of technology, an M.S. in operations research, and graduate certificates for chief information officer and IT program management.
Jay is a lifelong learnerāa member of the first cohort to earn the 10-course specialization in data science by Johns Hopkins University on Coursera. He is an award-winning speaker who has presented internationally and provides pro bono data science expertise to numerous not-for-profit organizations to improve their operational insights. Connect with Jay Gendron at https://www.linkedin.com/in/jaygendron, visit http://jgendron.github.io/, or Twitter @jaygendron.
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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 Dataās 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 Dataās 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...
