BLACK LIVES MATTER
Join us and donate
The premier IDE for R
RStudio anywhere using a web browser
Put Shiny applications online
Shiny, R Markdown, Tidyverse and more
Do, share, teach and learn data science
An easy way to access R packages
Let us host your Shiny applications
A single home for R & Python Data Science Teams
Scale, develop, and collaborate across R & Python
Easily share your insights
Control and distribute packages
RStudio
RStudio Server
Shiny Server
R Packages
RStudio Cloud
RStudio Public Package Manager
shinyapps.io
RStudio Team
RStudio Workbench
RStudio Connect
RStudio Package Manager
rstudio::conf 2018 case study
Rapid prototyping data products using Shiny
February 26, 2018
Rapid Prototyping Data Products using Shiny – Companies are becoming more aware of the need to embrace data analytics, but going from an idea to a full-fledged data-driven product can be a long and expensive process. At TCB Analytics, we advocate for a rapid prototyping approach using Shiny, a web application framework for R. Shiny enables statisticians and data scientists to quickly develop dashboards, empowering them to bring their hypotheses to life. Putting a real data-driven prototype in the hands of the end user allows for better refining of requirements before passing off to a web development team. We discuss approaches for productionizing Shiny applications and best practices for integrating your software team into the rapid prototyping process.
Tanya Cashorali is the founding partner of TCB Analytics, a Boston-based data consultancy. Previously, she worked as a data scientist at Biogen. Tanya started her career in bioinformatics and has applied her experience to other data-rich verticals such as telecom, finance, and sports. She brings over 10 years of experience using R in data scientist roles as well as managing and training data analysts, and she’s helped grow a handful of Boston startups.