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


You completed the first step in your journey and should be pleased with yourself as ETL is not trivial or simple. In this chapter, you learned how to execute an ETL process from start to finish. This includes knowing how to extract data from multiple sources, including databases. Then, you transformed the data with the dplyr package and exported the information into a file that could be loaded into a business system.

In the next chapter, you will learn how to clean data once it is loaded. You will see that, like ETL, data cleaning is a broad and multi-faceted aspect of business intelligence and analytics.