February 10, 2022
Update, Deploy, Authenticate and Share Insights
February 3, 2022
With RStudio Team, data scientists can build and share their work within an integrated architecture.
January 27, 2022
RStudio Workbench is the enterprise-level IDE for data scientists who need to develop, collaborate, and scale in R and Python.
September 22, 2021
This release adds new management, service, and configuration options to RStudio Package Manager. Highlights include a more versatile repository calendar, more flexibility in serving multiple binary package versions, and more options for configuring git sources.
June 2, 2021
RStudio Server Pro is now RStudio Workbench. With growing support for a wide range of development environments, we believe this new release is the best single platform to support open source, code-first data science, whether your team is using R or Python.
April 6, 2021
In case you missed the details of our recent release or would just like a quick tour, here's a set of videos highlighting our recent work on RStudio 1.4.
April 1, 2021
Continuing our series on self-service BI tools and code-first, open source data science, we explore embedded analytics and why they are a critical way for a data science team to deliver insights. We also discuss the unique needs that will be demanded of data science teams as they deliver insights that are secure, scalable, and flexible to multiple end user’s needs.
January 19, 2021
RStudio 1.4 has now officially been released. We think this is a must-have upgrade because it delivers credible, agile, and durable tooling for serious data science.
November 19, 2020
RStudio analyzes how the California Department of Public Health built a COVID-19 dashboard in R and Shiny that now serves millions of California citizens.
September 17, 2020
Lara Zaremba, a student at Goethe University, shares her experiences using RStudio Cloud to learn data science and how it has empowered her to help teach others.
July 9, 2020
Data Science presents challenges in the iteration of new research, unique business requirements, multiple technologies, accountability of results, and finding lasting solutions. Learn how an Integrated Development Environment (IDE) built for Serious Data Science tackles these issues head-on.
