RStudio’s mission is to create free and open-source software for data science, and at the core of this mission is a focus on a code-first approach. Data scientists grapple every day with novel, complex, often vaguely-defined problems with potential value to their organization. These sorts of problems are most easily approached with code. Learn more.
February 8, 2022 |
Michael Lippis of The Outlook podcast interviewed RStudio's Lou Bajuk to discuss the relationship between data science and business intelligence tools.
October 14, 2021 |
We interviewed Vergil Weatherford from Guidehouse to learn why they are planning to hire a Senior Shiny Deployment Engineer. Weatherford believes data science teams can benefit from someone who can apply software development best practices to support the deployment of high-quality R and Python applications into production.
September 16, 2021 |
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 impact at hundreds of organizations. In this post, we will focus on the advantages of code-first data science.
July 15, 2021 |
We recently sat down with Art Steinmetz, former CEO of OppenheimerFunds, to get his unique perspective on the value and viability of code-first, open source data science for the enterprise.
June 17, 2021 |
Supply chain management presents a number of interesting and challenging problems to solve in topics such as demand and supply planning, inventory management, and forecasting. This post dives into questions from the R in Supply Chain Management meetup with Nicolas Nguyen.
May 12, 2021 |
While you may already be a practitioner of code-first data science with R or Python, chances are you work within a larger organization with many analytic tools. In this post, we give you some advice on navigating this landscape, and convincing others in your organization of the value of code-first data science.