London, 26th March 2019 – QBS Distribution signs an agreement with RStudio. RStudio provides free and open source tools for data science and enterprise-ready professional software for teams. QBS Distribution is pleased to add RStudio’s flagship professional products RStudio Server Pro, RStudio Connect, and RStudio Package Manager to its leading software delivery platform for IT and to help professional data science teams develop and share their work at scale. Dave Stevinson, QBS Distribution managing director commented, “An increasing number of enterprises are using RStudio to make sense of their data. We live in a world of increasing data volumes and having tools that support an enterprise in understanding the data they create to support decision making is a point of competitive advantage.” Dave continued “RStudio is a perfect addition to the QBS Distribution software delivery platform to support our EMEA reseller community and their customers in making sense of their data!” Jim Clemens, VP Customer Success at Studio commented “Through their established customer relationships and positive reputation, QBS Distribution has demonstrated significant value as a partner and we are glad to be part of their solution.” About RStudio RStudio is the premier IDE for R, an open source language and environment for statistical computing and graphics. RStudio Server Pro delivers the team productivity, security, centralized management, metrics, and commercial support that professional data science teams need to develop at scale. RStudio Connect connects data scientists with decision makers. Publish Shiny applications, R Markdown reports, dashboards, Plumber APIs, Python notebooks, and more in one convenient place. Use push-button publishing, scheduled execution of reports, and flexible security policies to bring the power of data science to your entire enterprise. RStudio Package Manager is the package management system optimized for R and RStudio. Organize, search, and browse R packages within your team and across your organization. Access all of CRAN or define curated subsets. Add your local packages and packages from Github. Control and manage all of the packages that your data scientists and data products depend on.
