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

Chapter 6. Time Series Analysis

Time series analysis is the most difficult analysis technique presented in this book. One may argue that it does not belong in an introductory book. It is true that this is a challenging topic. However, one may also argue that an introductory awareness of a difficult topic is better than perfect ignorance of it. Time series analysis is a technique designed to look at chronologically ordered data that may form cycles over time. Key topics covered in this chapter include the following:

  • Analyzing time series data with linear regression

  • Introducing key elements of time series analysis

  • Building ARIMA time series models

Time series analysis is an upper-level college statistics course. It is also a demanding topic taught in econometrics. This chapter provides you with an understanding of a useful but difficult analysis technique. It provides a combination of theoretical learning and hands-on practice. The goal is to provide you with a basic understanding of working with...