RStudio is a full-featured programming environment for coding in R and, as it comes for free, it’s totally in scope for our Open Analytics duties. The best known version of this nice piece of software is the desktop one, which is available for Windows, Mac and Linux platforms and it’s not uncommon to see as a personal analytics solution, especially where SAS is way to expensive. Sometimes, people use RStudio to work locally with R, for developing/prototyping/testing and then deploy .R files on a remote (heavy) server which runs it using stand-alone R for better performance.
The question is: why do that if one could use RStudio bigger brother, the RStudio server?
Before start exploring the deep cliffs of the quantitative marketing analysis, I would just like to share my personal set of best practices I always use for an effective dashboard design process. Altough these are focused to a typical marketing use case, these are totally generic as they provide a set of analytical starting points and some cooking recipes on how to approach the task of designing a visual reporting environment for your company.
In this step-by-step tutorial I’ll show you how to use Talend Open Studio and the Twitter Components Pack to connect to Twitter, do a simple REST query and build a trivial relevance report on top on it. There’re tons of similar Talend tutorials out there, but no one is focused on my Twitter components pack, which let you do queries and result parsing without writing a single line of custom code. So let’s go into this 101 crash course on how to download tweets and build a real-world analysis on it.