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

Visualizing data

Your journey into the world of visualization starts with this observation-numbers are explicit and objective, visuals are implicit and subjective. Hidden within the numbers, shapes, and colors is a message that is subject to the interpretation of the viewer. Realize what happens as the visual image transforms through our senses into an understanding. The brain will subconsciously pass judgement in determining what information is essential and what is supportive. Sight becomes perception. Perception becomes cognition and knowledge (Cairo, 2013).

Calling attention to information

If sight is perception, then data storytellers must consider how to use visual elements to call attention to the most critical information. According to Cairo (2013), The brain is much better at quickly detecting shade variations than shape differences (p. 113). He provides tips on how to call the user's attention to particular portions of a visual. First, he suggests using pure colors to highlight the...