Book Image

Introduction to R for Business Intelligence

By : Gendron
Book Image

Introduction to R for Business Intelligence

By: 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 (13 chapters)
9
A. References
11
C. R Packages Used in the Book
12
D. R Code for Supporting Market Segment Business Case Calculations

Conventions

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "You can load the Bike Sharing data file into the R environment by using the read.csv() function."

A block of code is set as follows:

bike$holiday <- factor(bike$holiday, levels = c(0, 1),
                       labels = c("no", "yes"))
bike$workingday <- factor(bike$workingday, levels = c(0, 1),
                          labels = c("no", "yes"))

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

query <- "SELECT * FROM marketing" 
bike <- sqlQuery(connection, query) 
close(connection)

Any command-line input or output is written as follows:

[1] TRUE

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "RStudio will automatically create a ui.R and server.R file, if you create a new project and choose New Directory and Shiny Web Application as the type."

Note

Warnings or important notes appear in a box like this.

Tip

Tips and tricks appear like this.