Book Image

Introduction to R for Business Intelligence

By : Jay Gendron
Book Image

Introduction to R for Business Intelligence

By: Jay 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 (19 chapters)
Introduction to R for Business Intelligence
About the Author
About the Reviewers
R Packages Used in the Book
R Code for Supporting Market Segment Business Case Calculations

Geo-mapping using Leaflet

Geo-mapping is the process of placing markers representing data in a geographic context, typically using latitude and longitude. Leaflet is an open source JavaScript library for building interactive geo-maps with ease. Why are we talking about a JavaScript mapping library in an R book? The R package leaflet is a wrapper around this JavaScript library that translates most of its functionality into a set of R functions. It allows analysts to visualize geospatial data easily. With this package, you can generate maps from within RStudio or embed them in R Markdown documents or Shiny web applications.


Use case: Geo-mapping Bike Stations

Remember when you supported management by creating a business case for the location of customer service kiosks? You had data on each of the 244 Bike Sharing stations throughout the city. Go ahead and pull this same data from the file called Ch7_bike_station_locations.csv, located on the book's website at