2021-09-16
Lou Bajuk
Three key attributes define Serious Data Science: open-source software, code-first development, and a centralized data science infrastructure. This approach has been successful at driving value and impact at hundreds of organizations. In this post, we will focus on the advantages of code-first data science.
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2021-09-07
Pritam Dalal
Pritam Dalal from the RStudio Customer Success team shares his perspective on the pros and cons of Excel vs. code-first data science, based on observations from his career in financial services.
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2021-08-27
Colin Gillespie (Jumping Rivers)
This is a guest post by Colin Gillespie from Jumping Rivers answering your questions from their most recent series of webinars, Practical Advice for Putting R in Production.
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2021-08-12
Michael Demsko
For the first piece in our new RStudio Voices series, we decided to interview one of our open source package developers, Julia Silge.
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2021-08-10
Matthias Mueller
In connection with R, Python, Slack and RStudio Connect, CM Group built a system that serves custom, individualized insights directly to stakeholders, at the right time, where work already happens.
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2021-08-03
Chris Bumgardner
The team at Children’s Wisconsin is using R and RStudio’s suite of tools to enable forecasting, modeling, and data mining among other data science activities. During the meetup, Chris Bumgardner shared a few examples of the applications that have been created to support their vision that the kids of Wisconsin will be the healthiest in the nation.
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2021-07-15
Lou Bajuk
We recently sat down with Art Steinmetz, former CEO of OppenheimerFunds, to get his unique perspective on the value and viability of code-first, open source data science for the enterprise.
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2021-07-12
Marcin Dubel (Appsilon)
We compared the features and capabilities of Shiny, Tableau, and PowerBI for delivering insights in enterprise organizations. This is our opinion on how they stack up.
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2021-06-24
Behrooz Hassani-Mahmooei (and the InSight Team)
Similar to any other large and complex organisation, Monash University employs a wide range of data to inform decision making and monitor different aspects of their operations.
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2021-06-15
Lou Bajuk
Data science teams sometimes believe that they must standardize on R or Python for efficiency, at the cost of forcing individual data scientists to give up their preferred, most productive language. RStudio’s professional products provide the best single home for R and Python data science, so teams can optimize the impact their team has, not the language they use.
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