RStudio
Open source and enterprise-ready professional software for the r statistical computing environment.
| Date | Investors | Amount | Round |
|---|---|---|---|
| - | investor investor | €0.0 | round |
| N/A | $161m | Late VC | |
| Total Funding | 000k | ||
| USD | 2019 | 2020 |
|---|---|---|
| Revenues | 0000 | 0000 |
| % growth | - | 25 % |
| EBITDA | 0000 | 0000 |
| Profit | 0000 | 0000 |
| EV | 0000 | 0000 |
| EV / revenue | 00.0x | 00.0x |
| EV / EBITDA | 00.0x | 00.0x |
| R&D budget | 0000 | 0000 |
Source: Dealroom estimates
Related Content
RStudio is a technology startup that specializes in providing solutions for data science teams to effectively utilize open-source programming languages, R and Python. The company's primary offerings include deployment of various data science projects such as Shiny, Streamlit, Dash applications, models, Quarto documents, Jupyter Notebooks, reports, dashboards, and APIs. These tools are designed to streamline the process of uploading, storing, accessing, and sharing data science work.
RStudio operates in the data science market, serving a broad range of clients across various industries. Its clientele includes professional data science teams, engineers, technologists, and data scientists. The company boasts of being trusted by 52 of the Fortune 100 companies, indicating its strong presence in the enterprise segment.
The business model of RStudio revolves around providing tools and solutions that help clients adopt open-source data science at scale. It offers customizable access controls and authentication options, ensuring secure sharing of data-science applications across teams and enterprises. The company also provides expertise to help clients maximize their investments in R and Python.
RStudio generates revenue by selling its solutions and services to its clients. While the specifics of its pricing strategy are not publicly available, it's reasonable to assume that the company charges clients based on the scale and complexity of their data science projects.
Keywords: Data Science, Open-Source, R Programming, Python, Data Deployment, Enterprise Solutions, Data Science Tools, Data Collaboration, Reproducible Results, Data Insights.