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

Summarizing your data for inspection

We live in an information age. Large and accessible datasets are being widely used in business intelligence and decision making. When you begin the data cleaning process, you will need a way of summarizing your data. You will need to understand its content and structure at the beginning of the process. Large datasets require ways of summarizing the data for inspection. Fortunately, the R language provides them for you! You will learn data cleaning through a use case called the Bike Sharing Analysis Project.


Use case: Bike Sharing Analysis Project

Imagine you are a business analyst on the Bike Sharing Analysis Project. New data has just arrived for analysis. Unlike the dataset you saw in Chapter 1, Extract, Transform, and Load, which was pre-processed for a Kaggle competition, this data you received has arrived in raw form. The book's website at contains the Ch2_raw_bikeshare_data.csv data. Before...