What is Posit Workbench? || Posit

Data science teams work in diverse technical environments with many data sources, coding tools, computational requirements, and client expectations for data products. Having this work spread across multiple systems creates inefficient work silos and introduces critical gaps in security.

What is Posit Workbench?

RStudio Workbench addresses all of this by providing IT the ability to manage and scale data ingestion, analysis, and data product creation securely, all from one place, while providing data scientists the ability to collaborate on R and Python projects, whether RStudio with its ability to run multiple versions of R in different sessions, or JupyterLab, or Jupyter Notebooks, or VS Code, each with the option of running pre-configured data connectors, requesting compute resources, and providing the ability to collaborate with in a shared environment.

If they choose to use the RStudio IDE, team members can share projects and track work in real time, helping to keep up with changes and supporting best practices for code review, which ultimately allows data science leaders to build happy and effective teams while delivering value to their stakeholders. Using RStudio Workbench, the data science team can create reports, dashboards, and interactive applications for their organization's decision makers, which can be hosted on platforms such as RStudio Connect.

delivering value to their stakeholders.

Moving work off the local laptop

By moving work from the local laptop and onto RStudio Workbench, users can quickly authenticate and spin up the coding environment of their choice for either R or Python, providing easy access to pre-configured data connectors like Snowflake, MongoDB, and Spark, just to name a few. Your team can also request critical compute resources that they won't likely have access to on local systems, with different user or group profiles for default and max resource usage, which helps to control cost.

RStudio Workbench makes it easier for teams to work together by providing a standardized set of installed software, which helps ensure that data science work is reproducible between team members, and integration with Git supports collaboration and code governance across coding environments.

RStudio Workbench. Enable your team to build great data science products.