Introduction to R for Business Intelligence

Jay Gendron

• Publisher: Packt Publishing
• Year: 2016
• ISBN:
  9781785280252
• Edition: 1
• Topic: Informatica
• Subtopic: Elaborazione di dati

Learn how to leverage the power of R for Business Intelligence

About This Book

• Use this easy-to-follow guide to leverage the power of R analytics and make your business data more insightful.
• This highly practical guide teaches you how to develop dashboards that help you make informed decisions using R.
• Learn the A to Z of working with data for Business Intelligence with the help of this comprehensive guide.

Who This Book Is For

This book is for data analysts, business analysts, data science professionals or anyone who wants to learn analytic approaches to business problems. Basic familiarity with R is expected.

What You Will Learn

• Extract, clean, and transform data
• Validate the quality of the data and variables in datasets
• Learn exploratory data analysis
• Build regression models
• Implement popular data-mining algorithms
• Visualize results using popular graphs
• Publish the results as a dashboard through Interactive Web Application frameworks

In Detail

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.

Style and approach

This book will take a step-by-step approach and instruct you in how you can achieve Business Intelligence from scratch using R. We will start with extracting data and then move towards exploring, analyzing, and visualizing it. Eventually, you will learn how to create insightful dashboards that help you make informed decisions—and all of this with the help of real-life examples.

Introduction to R for Business Intelligence

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Introduction to R for Business Intelligence

Copyright © 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.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

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

Credits

Author Jay Gendron	Copy Editor Vibha Shukla
Reviewers Fabien Richard Jeffrey Strickland, Ph.D.	Project Coordinator Nidhi Joshi
Commissioning Editor Veena Pagare	Proofreader Safis Editing
Acquisition Editors Usha Iyer Manish Nainani	Indexer Aishwarya Gangawane
Content Development Editor Siddhesh Salvi	Graphics Disha Haria
Technical Editor Pranil Pathare	Production Coordinator Nilesh Mohite

About the Author

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 learner—a 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.

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...