Data scientist using R and Python

Analytics Executive

Ensure your analytics teams are collaborating effectively, and using the best tools for each analytic job

As an Analytics Executive, your most important priority is ensuring that your organization can effectively tackle its analytic challenges, and get the most value out of the data you collect, while managing costs and complexity. When analytics teams fail to collaborate and share their work efficiently, that means lost opportunities for your organization, and unnecessary expense.

RStudio promotes collaboration between your BI and Data Science teams, and help enable your organization to use the right approach for any given analytic problem, so that you can deliver the best of both analytic worlds.

Learn more:

  • Match your analytic approach to your specific applications, to avoid being trapped in a false choice between BI and Data Science approaches.
  • Understand the strengths and challenges of both self-service BI and open source data science, so you can help your organization navigate this complex analytic landscape.
  • Enable your data science team to build applications, reports and dashboards tailored to the specific needs of your most critical decision makers, with fully custom, R- or Python-based analytic applications using RStudio Connect, to complement your standard BI reporting.
  • Read this customer story to learn how Brown-Forman used RStudio products to help their data science team “turn into application developers and data engineers without learning any new languages or computer science skills.”

Augment your BI tools with Serious Data Science

While data science and BI teams share the same goals, to help their organizations make better decisions by getting the most valuable insights possible out of their data, each approach has distinct strengths and challenges. By leveraging Data Science tools to augment your BI investments, you can maximize the value of the insights you deliver to your decision-makers.

RStudio helps break down analytic silos and enhance an organization's analytic investments, so that all members of the data organization (BI analysts, data scientists, ML engineers, data engineers) can collaborate, get deeper insights, support better decision making and drive results.

RStudio Team not only provides a single home for data science teams using R and Python, it enables Data Science teams to augment the great work that BI teams provide:

  • Enrich your data using R and Python, for visualization and exploration in BI tools. Read more about Data Handoffs
  • Build tailored applications using open source frameworks such as Shiny, Dash and Streamlit, and share them with your business users to complement standard BI reporting. Read more about RStudio Connect
  • Securely call R and Python APIs from Tableau dashboards, to make the models, forecasts and other insights from your data science team available on demand. Read more about RStudio Connect and Tableau
  • Easily embed interactive Shiny applications in Tableau, to augment Tableau's standard visualizations and leverage the visual insights your data science team develops. Read more about ShinyTableau
  • Augment your BI tools existing R and Python integrations: Many BI tools have some form of integration with R or Python. RStudio Teams provides a secure, scalable, collaborative development environment for your data science teams to develop the open source code for deployment in your BI tools, as well as a way of managing your open source package use to ensure consistency and reproducibility across all your analytics platforms.

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