Why Your Enterprise Needs Code-First Data Science
An RStudio webinar presentation
Lou Bajuk
Nick Rohrbaugh
Tuesday, April 27th at 1pm ET
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What You'll Learn
As a data scientist, or as a leader of a data science team, you are probably well aware of the power and flexibility that open source data science, based on R and Python, provides you and your team. However, your team probably exists within a typical enterprise, which has a wide variety of analytic tools, including self-service BI, point-and-click data science tools, and R and Python. Navigating this landscape, and convincing others in your organization of the value of open source data science, can be challenging.
In this webinar, we will explain why a modern enterprise needs code-first data science, and how it fits in with your organization's other investments:
- Serious Data Science: based on open source R and Python, code-first, and centralized on prem or in the cloud, for ease of access, scalability and management.
- The Power of Code: reusable, extensible, reproducible, and inspectable data science.
- Interoperability: how code-first data science complements and helps your organization take better advantage of all its analytic investments, including mixed teams of R and Python data scientists, a wide variety of data sources, BI tools and job management clusters such as Kubernetes and Slurm.
After this webinar, you will have the tools to be an advocate in your organization for the value of R and Python data science, scaled and operationalized by RStudio's pro products.
About the speakers
Lou Bajuk
/Sr. Director, Product Marketing at RStudio
Lou is a passionate advocate for data science software, and has had many years of experience in a variety of leadership roles in large and small software companies, including product marketing, product management, engineering and customer success. In his spare time, his interests includes books, cycling, science advocacy, great food and theater.
Nick Rohrbaugh
/Customer Success, Financial Services
Nick helps customers make the most of RStudio’s products. His background is in cognitive psychology, where he first developed his love for all things RStudio. Before joining RStudio, he worked to improve geopolitical forecasting with Good Judgment.