Most Recent: Data Science Leadership
Latest: Data Science Leadership
In this post, we walk through the tools and functionality we used to automate survey results reporting.
Many tools used routinely by software developers can also be useful to data scientists.
In this post, we explore possible challenges to putting Shiny in production and how to overcome them.
We are excited to introduce rstudio.com/champion, a website with resources and best practices for making the case for data science at your organization.
Alan Carlson from Snap Finance describes how his team uses a reproducible workflow to build robust, modular dashboards that streamline onboarding and minimize technical debt.
Last year, a group from RStudio flew out to Iceland to capture the story of how Reykjavík's data science team improves the lives of their city's citizens.
Michael Lippis of The Outlook podcast interviewed RStudio's Lou Bajuk to discuss the relationship between data science and business intelligence tools.
Marcin Dubel from Appsilon shares key considerations for creating an award-winning Shiny application.
In this blog post, we highlight three speakers from the RStudio Enterprise Community Meetup who share packages and tools to supercharge your R skills.
2021 INSPIRE U2 participants Kathleen Bostic and Michel Ruiz-Fuentes reflect on their experience in the program, where they developed their data science skills with the support of faculty and...
Three key attributes define Serious Data Science; open-source software, code-first development, and a centralized data science infrastructure. This approach has been successful at driving value and...
Georgia Institute of Technology faculty, scientists, GIS specialists, and graduate students share their experience launching a Shiny application that was used by over 8 million people around the...
Pritam Dalal from the RStudio Customer Success team shares his perspective on the pros and cons of Excel vs. code-first data science, based on observations from his career in financial services.