Chapter 8 Communication of Analytics: An Rmarkdown Approach

Learning Objectives

By the end of this chapter, students should have learned the importance of communication in data science and particulary in auditing and accounting. The students should specifically learn the following:

  1. The importance of communication in data science.
  2. The importance of communication in Auditing
  3. What Shiny is
  4. How Shiny could improve the communication of data/audit analytics.

8.1 What is Rmarkdown

RMarkdown enables analysts to engage with code interactively, embrace literate programming, and rapidly produce a wide variety of high-quality data products such as documents, emails, dashboards, and websites. Emily Riederer2, an analytics manager at Capital One, describes how reproducible programming using RMarkdown can help R users develop better software programming practices.

Use the following website to develop this chapter - https://m-clark.github.io/Introduction-to-Rmarkdown/

Another good Website -

https://rpubs.com/thealk/academic-writing This one is one of the best - https://rc2e.com/rmarkdown

For other forms of communication of analytics - https://rmd4sci.njtierney.com/different-outputs-and-extensions.html

  1. https://rstudio.com/resources/rstudioconf-2020/rmarkdown-driven-development/↩︎