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Introduction to R for Business Intelligence

You're reading from   Introduction to R for Business Intelligence Profit optimization using data mining, data analysis, and Business Intelligence

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Product type Paperback
Published in Aug 2016
Publisher Packt
ISBN-13 9781785280252
Length 228 pages
Edition 1st Edition
Languages
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Author (1):
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Jay Gendron Jay Gendron
Author Profile Icon Jay Gendron
Jay Gendron
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Table of Contents (13) Chapters Close

Preface 1. Extract, Transform, and Load FREE CHAPTER 2. Data Cleaning 3. Exploratory Data Analysis 4. Linear Regression for Business 5. Data Mining with Cluster Analysis 6. Time Series Analysis 7. Visualizing the Datas Story 8. Web Dashboards with Shiny A. References
B. Other Helpful R Functions C. R Packages Used in the Book
D. R Code for Supporting Market Segment Business Case Calculations

Deploying your Shiny app


Once you have created Shiny apps, you will want to share them with a broader audience. The following are three ways that are available to you:

  • Located on GitHub

  • Hosted on RStudio

  • Hosted on a private web server

Each of these three options has its advantages and disadvantages based on your desired implementation, but you should typically find that one of the three suits your needs better than the others.

Located on GitHub

First, you might want to share with another R-savvy user. There are three options to run an app from a location online or a locally-cloned repository. For example, you can run the online version of the campaign creator Shiny app by opening R and running a code block pointing to its location on GitHub:

shiny::runGitHub(repo = "com.packtpub.intro.r.bi", 
     username = "jgendron", 
     subdir = "Chapter8-ShinyDashboards/Ch8-CampaignCreatorApp") 

This method is extremely helpful when exploring various applications that others have created and you would like...

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