BI and Data Science
For Data Scientists
Serious Data Science
The Ease of Use
of Self-Service BI
Increase your impact on decision making by collaborating with BI teams
As a Data Scientist, you grapple daily with novel, potentially valuable, sometimes vaguely-defined problems that require extensive data preparation and a wide range of advanced analytic methods and visualizations to solve. That's why you use languages like R and Python.
But when BI tools are used widely in your organization, you might find yourself competing with those tools to get your insights out to the wider organization where they can have an impact on decision making, or find yourself forced to awkwardly use the unfamiliar data science integrations that the BI tools provide.
By leveraging RStudio, you can effectively collaborate with your BI colleagues and increase the visibility and impact of your work.
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:
“Power BI is an easy to build visualization tool widely used in our organization to make data accessible to non-data people. This is a really great tool when we want to create a dashboard for trends and track some metrics. But it becomes very difficult when we want to enable high levels of user interactivity with the dashboard. That’s where R Shiny helped us to build intuitive and highly interactive user interfaces.”
– A marketer at a large telecommunications firm
“RStudio is code based, so in the beginning tools like Spotfire and Tableau have [their] advantages since many things are already built in, but in terms of flexibility RStudio will win over the longer term.“
– A team lead in a biotech company
“Most of the work the data scientists did used the R language. They did a great job satisfying management’s constant barrage of questions because iterative analysis is so easy with tools like R, and the powerful visualization tools made communication of results easy for sales people to grasp. As the CEO, I was gratified at how clear the presentations were and at how quickly presenters answered my difficult questions, in some cases on the fly during the presentations.
As an R user myself, I know its code-based workflow lends itself to rapid iteration while, at the same time, documenting the process used. It was easy to unroll the tape to see every step that led to any conclusion.”
– Art Steinmetz, former Chairman and CEO of Oppenheimer Funds
“The R ecosystem has vast power to quickly solve problems. With R, I can incorporate nearly any AI/ML model into a dashboard or Shiny app, without being reliant on proprietary data science tools. Executives can be confident I am using the best analytic approach for a given problem, and I can rapidly apply new approaches as they become available.”
– Paul Ditterline, Director of Data Science at Heaven Hill Brands