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  • Book Overview & Buying Introduction to R for Business Intelligence
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Introduction to R for Business Intelligence

Introduction to R for Business Intelligence

By : Gendron
Buy this Book
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Introduction to R for Business Intelligence

Introduction to R for Business Intelligence

By: Gendron
Buy this Book

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 (13 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
Lock Free Chapter
1
1. Extract, Transform, and Load
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1. Extract, Transform, and Load
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Understanding big data in BI analytics
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Extracting data from sources
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Transforming data to fit analytic needs
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Loading data into business systems for analysis
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Summary
2
2. Data Cleaning
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2. Data Cleaning
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Summarizing your data for inspection
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Finding and fixing flawed data
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Converting inputs to data types suitable for analysis
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Adapting string variables to a standard
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Summary
3
3. Exploratory Data Analysis
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3. Exploratory Data Analysis
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Understanding exploratory data analysis
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Analyzing a single data variable
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Analyzing two variables together
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Exploring multiple variables simultaneously
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Summary
4
4. Linear Regression for Business
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4. Linear Regression for Business
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Understanding linear regression
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Checking model assumptions
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Using a simple linear regression
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Refining data for simple linear regression
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Introducing multiple linear regression
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Summary
5
5. Data Mining with Cluster Analysis
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5. Data Mining with Cluster Analysis
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Explaining clustering analysis
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Partitioning using k-means clustering
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Clustering using hierarchical techniques
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Summary
6
6. Time Series Analysis
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6. Time Series Analysis
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Analyzing time series data with linear regression
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Introducing key elements of time series analysis
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Building ARIMA time series models
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Summary
7
7. Visualizing the Datas Story
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7. Visualizing the Datas Story
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Visualizing data
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Plotting with ggplot2
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Geo-mapping using Leaflet
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Creating interactive graphics using rCharts
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Summary
8
8. Web Dashboards with Shiny
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8. Web Dashboards with Shiny
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Creating a basic Shiny app
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Creating a marketing-campaign Shiny app
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Deploying your Shiny app
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Summary
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A. References
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A. References
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B. Other Helpful R Functions
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B. Other Helpful R Functions
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Chapter 1 - Extract, Transform, and Load
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Chapter 2 - Data Cleaning
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C. R Packages Used in the Book
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C. R Packages Used in the Book
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D. R Code for Supporting Market Segment Business Case Calculations
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D. R Code for Supporting Market Segment Business Case Calculations

What you need for this book

You need the R statistical package, available free as an open source download from CRAN (https://www.r-project.org/). This book used R version 3.3.1 for Windows. You will get the same results using the macOS or Linux software.

Optionally, it is also recommended that you use RStudio Desktop, an open source user interface that works with R (https://www.rstudio.com/). This book used version 0.99.903 for Windows. It is also available for macOS and Linux.

Lastly, you will need to install a variety of R packages to perform the various analyses. All these are all freely available using the install.packages() function within R. You can get a refresher on installing packages in Appendix C, R Packages Used in the Book.

This book provides code using the R statistical programming language. Perhaps it has been a while since you last used or learned R. If that is the case, then you may find the following material quite useful. It provides a listing of R skills that you should know before working on the use cases provided in each of the chapters.

Video links (Peng, 2015; Peng, 2014; LawrenceStats, 2016; Peng, 2012) for each skill provide an explanation of techniques that you may want to review before continuing:

Skill

Chapter

Video resource

Installing R

1

Windows: https://www.youtube.com/watch?v=Ohnk9hcxf9M

macOS: https://www.youtube.com/watch?v=uxuuWXU-7UQ

Installing R Studio

1

Windows and macOS: https://www.youtube.com/watch?v=bM7Sfz-LADM;feature=youtu.be;t=10s

Installing R packages

1

https://www.youtube.com/watch?v=H3EFjKngPr4

Setting working directory

1

Windows: https://www.youtube.com/watch?v=XBcvH1BpIBo

macOS: https://www.youtube.com/watch?v=8xT3hmJQskU

Data types

1

Part 1: https://www.youtube.com/watch?v=vGY5i_J2c-c

Part 2: https://www.youtube.com/watch?v=w8_XdYI3reU

Part 3: https://www.youtube.com/watch?v=NuY6jY4qE7I

Basic scripting

1

Control structures (part 1): https://www.youtube.com/watch?v=8RmwEBo8yy0

Control structures (part 2): https://www.youtube.com/watch?v=z8V-a6d8JTg

Basic plotting

2

Base plotting (part 1): https://www.youtube.com/watch?v=AAXh0egb5WM

Base plotting (part 2): https://www.youtube.com/watch?v=bhyb1gCeAVk

Subsetting data

2

Subsetting basics: https://www.youtube.com/watch?v=VfZUZGUgHqg

Subsetting matrices: https://www.youtube.com/watch?v=FzjXesh9tRw

CONTINUE READING
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Tech Concepts
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Programming languages
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