Boosting your R development with Databricks
- R Studio
- Spark R
As organizations increasingly focus on machine learning and artificial intelligence, R is fast becoming one of the most popular programming languages. However, in this new world of big-data-analysis and cloud technology, the traditional RStudio environment can become a bottleneck on large-scale analytics projects.
Databricks, a unified data analytics platform, can provide a great solution. Powered by a distributed Spark processing framework, it supports scalable data analytics through common programming interfaces including R. In this webcast we present three common scenarios that enterprises are using to evaluate migrating R on Databricks, from users continuing using the familiar RStudio environment backed by a Databricks cluster, through to shifting their full operation into Databricks. In this recorded webcast, Thorogood Consultant Robbie Shaw covers the benefits and drawbacks you’ll need to consider before selecting which scenario works for you when making the transition to running R on Databricks.
This webcast covers:
- An overview of R in Databricks
- RStudio on Databricks
- Databricks Connect with RStudio Desktop
- SparkR and sparklyr
Is it for you?
- Do you use the R programming language?
- Is running RStudio on your laptop slowing your progress?
- Do you want to transition R analysis to the cloud?
- Are you currently using Databricks and want to expand its capability?
- Do you work with other integrated development environments and want to see how Databricks Connect could help you leverage a Spark engine?