Introduction to R for Business Intelligence

封面

版权页

Credits

About the Author

Acknowledgement

About the Reviewers

www.PacktPub.com

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Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Chapter 1. Extract Transform and Load

Understanding big data in BI analytics

Extracting data from sources

Transforming data to fit analytic needs

Loading data into business systems for analysis

Summary

Chapter 2. Data Cleaning

Summarizing your data for inspection

Finding and fixing flawed data

Converting inputs to data types suitable for analysis

Adapting string variables to a standard

Summary

Chapter 3. Exploratory Data Analysis

Understanding exploratory data analysis

Analyzing a single data variable

Analyzing two variables together

Exploring multiple variables simultaneously

Summary

Chapter 4. Linear Regression for Business

Understanding linear regression

Checking model assumptions

Using a simple linear regression

Refining data for simple linear regression

Introducing multiple linear regression

Summary

Chapter 5. Data Mining with Cluster Analysis

Explaining clustering analysis

Partitioning using k-means clustering

Clustering using hierarchical techniques

Summary

Chapter 6. Time Series Analysis

Analyzing time series data with linear regression

Introducing key elements of time series analysis

Building ARIMA time series models

Summary

Chapter 7. Visualizing the Datas Story

Visualizing data

Plotting with ggplot2

Geo-mapping using Leaflet

Creating interactive graphics using rCharts

Summary

Chapter 8. Web Dashboards with Shiny

Creating a basic Shiny app

Creating a marketing-campaign Shiny app

Deploying your Shiny app

Summary

Appendix A. References

Appendix B. Other Helpful R Functions

Chapter 1 - Extract Transform and Load

Chapter 2 - Data Cleaning

Appendix C. R Packages Used in the Book