Carl Howe is the Director of Education at RStudio and has been a dedicated R user since 2002. Carl leads a team of professional educators and data scientists at RStudio whose mission to train the next million R users globally. Carl regularly teaches workshops on topics such as reproducible R Markdown and RStudio’s Pro products to help R beginners become productive more quickly. Carl lives with his wife Carolyn in Stow, Massachusetts at the pleasure of his two cats.
February 1, 2021
The 24 hours of rstudio::global(2021) may be over, but you can still catch up on the talks you missed. Replay all the global keynotes and talks at rstudio.com.
January 20, 2021
The 24 hours of rstudio::global(2021) start tomorrow! Register now if you haven't and enroll for the sessions that are most convenient for your local time.
January 7, 2021
Only 2 days left before our survey closes! Please fill out our 3nd annual survey so that we can better understand today's R community. We'll publish the results in February 2021 as free and open source data.
January 6, 2021
In this post, I continue our series on how to create your own Google Analytics dashboard in R. Using the data we downloaded in our last post, we'll now create a simple dashboard showing blog page views over time and highlighting the most popular ones.
December 11, 2020
Want data about how people learn and use R? If so, please fill out our 3nd annual survey so that we can better understand today's R community. We'll publish the results in February 2021 as free and open source data.
November 27, 2020
This article, the first of three, describes how to use a code-oriented data science approach to Google Analytics data from a blog. It creates custom views of raw GA data while hiding the complexity of the Google Analytics data and interface
November 17, 2020
Michael Lippis of The Outlook podcast recently interviewed RStudio's Lou Bajuk to discuss open source data science, support for R and Python, and how leaders are getting value from data science.
October 30, 2020
When our customers ask us why RStudio's products support Python as well, we have a simple answer: It's because our data shows that our customers use R and Python for different tasks
September 23, 2020
To help address some of the uncertainty data science leaders may be feeling heading into the fall planning season, we note three new resources to help your team learn new skills and communicate their value better.
September 10, 2020
In this post, we answer questions raised by participants and attendees during our recent Debunking R & Python Myths webinar. Our bottom line was to use the tools that let you be most productive in the shortest amount of time.
September 4, 2020
We offer 3 entertaining Shiny apps plus a bonus app from our 2nd Annual Shiny Contest that will help you forget work over Labor Day weekend
August 27, 2020
Data scientists frequently have computational needs that stretch far beyond their laptops. Data science leaders should embrace features of RStudio Server that give data scientists access to shared IT resources without breaking the bank
August 26, 2020
For data science to be credible, agile and durable, we need to embrace the differences between R vs. Python.
July 28, 2020
In this post I present three "wild-caught" examples solicited from the R community of how they use interoperability between R, Python and other languages to solve real-world problems.
July 15, 2020
No single platform meets all the analytic needs of every organization. To avoid productivity-sapping complexity and underutilized infrastructure, encourage Interoperability so that your data scientists can access everything they need from their native tools.
July 7, 2020
RStudio will be focusing on interoperability in this blog during the month of July, highlighting how data scientists are using other tools with R to perform their work.
June 24, 2020
Delivering persistent value over the long haul from your data science team requires reusability, reproducibility, and up-to-date insights, built on a sustainable platform.
June 9, 2020
Data science teams struggle to deliver results quickly. Agile techniques such as rapid iteration and continuous collaboration with stakeholders can help overcome these challenges.
June 2, 2020
For Data Science to be applied, decision makers must trust and accept the insights. Your team needs the tools to find relevant insights, and to communicate these insights in a way that builds trust and understanding.
May 27, 2020
A slew of new vendors believe that no-code analytics and visualization tools can replace the role of the traditional data scientist. This brief describes why we believe organizations will demand pro-code data scientists for years to come.
February 6, 2020
More people are learning data science every day, and there are more ways for them to learn than ever before.
January 25, 2019
Many students believe that R is obscure, complex, and difficult to write. However, data from a new large-scale survey of R users conducted by RStudio shows that new R users are taking...
