Reflection of being a three-years RStudio user.
December 20, 2020

Reflection of being a three-years RStudio user.

Anonymous | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with RStudio

The decision of technology has been divided by corporate and teams. RStudio is a department-based decision, which has been selected by our director and carried out through. However, we also have team members use Python predominantly. We used RStudio to prepare markdown notes, slides, reports, and ranges of analysis around the organization, including admission, human resource, finance budgeting, etc. Currently, the most important outcome is reporting to senior management teams.
  • Reproducibility for repetitive reports.
  • Endless choices of open source packages supporting integration with data lake and data warehouse.
  • Flexibility of customise visualisation.
  • Python is quite popular in the industry, though the package rticulate is available to support integration, there is still room to improve.
  • Environment management (package and R versions) is complex, or need to purchase paid functionality on Mac.
  • We easily saved multiple FTE (full time equivalent)/headcount on analysis.
  • Everything is recorded and saved on GitLab, so with personnel change, the downtime becomes minimum.
I used them to run Python codes, so that not really comparable here. I will describe my experience around it. I feel that Jupyter Notebook is the closest product to RMarkdown file, as it allows users to run line by line and share outcomes underneath. PyCharm and Visual Studio are loved by developers mostly.

RStudio has benefits as it has more options, such as RMarkdown, shiny app, normal script, and etc. While other options mostly just have one appearance.
Well suited:

The vice-chancellor is asking for updates of how the student admission pipeline looks. This will be enabled by RStudio where daily patterns can be reproduced by day, and supporting defects identification and etc.

Less appropriate:

  • Hosting data collection: for example, collecting individual students information and insert into the database, or
  • Manipulating database structure: for example, dropping a table or merge tables to be stored in the database.