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Introduction to R for Business Intelligence

You're reading from Introduction to R for Business Intelligence Profit optimization using data mining, data analysis, and Business Intelligence

Product type Paperback

Published in Aug 2016

Publisher Packt

ISBN-13 9781785280252

Length 228 pages

Edition 1st Edition

Languages

R

Concepts

Business Intelligence

Author (1):

Jay Gendron

View More author details

Table of Contents (13) Chapters

Preface

1. Extract, Transform, and Load FREE CHAPTER

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

A. References

B. Other Helpful R Functions

C. R Packages Used in the Book

D. R Code for Supporting Market Segment Business Case Calculations

Appendix A. References

The following is a list of references used throughout the book, starting from the Preface and including the chapters:

Preface:

Guerra, P. & Borne, K. (2016, February). Ten Signs of Data Science Maturity. Sebastopol, CA: O'Reilly Media, Inc.

LawrenceStats. (2016, March 22). RStudio Basics: Install & Load an R Package [Video file]. Retrieved from https://www.youtube.com/watch?v=H3EFjKngPr4 .

Peng, R. (2012a). Setting Your Working Directory and Editing R Code (Mac) [Video file]. Retrieved from https://www.youtube.com/watch?v=8xT3hmJQskU .

Peng, R. (2012b). Setting Your Working Directory and Editing R Code (Windows) [Video file]. Retrieved from https://www.youtube.com/watch?v=XBcvH1BpIBo .

Peng, R. (2014a). Base Plotting part 1 [Video file]. Retrieved from https://www.youtube.com/watch?v=AAXh0egb5WM .

Peng, R. (2014b). Base Plotting part 2 [Video file]. Retrieved from https://www.youtube.com/watch?v=bhyb1gCeAVk .

Peng, R. (2014c). Control Structures...

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Authors (1)

Gendron

Gendron

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 learnera 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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