We have already seen some love from Tableau for R and Python, boosting Tableau’s Advanced Analytics capabilities.
So what is the next big thing for our Data Science Rockstars? Julia!
Who is Julia?
Julia is a high-level dynamic programming language introduced in 2012. Designed to address the needs of high-performance numerical analysis its syntax is very similar to MATLAB. If you are used to MATLAB, you will be very quick to get on track with Julia.
Compared to R and Python, Julia is significantly faster (close to C and FORTRAN, see benchmark). Based on Tableau’s R integration, Julia is a fantastic addition to Tableau’s Advanced Analytics stack and to your data science toolbox.
Where can I learn more?
Do you want to learn more about Advanced Analytics and how to leverage Tableau with R, Python and Julia? Meet me at the 2017 Tableau Conferences in London, Berlin or Las Vegas and join my Advanced Analytics sessions:
Will there be an online tutorial?
Yes, of course! I published tutorials for R and Python on this blog. And I will also publish a Julia tutorial soon. Feel free to follow me on Twitter @xlth, and leave me your feedback/suggestions in the comment section below.
Further reading: Mastering Julia
A German translation of this post is published on the official Tableau blog: Tableau Conference On Tour Sneak Peek: Julia-Integration für Advanced Analytics
[Update 11 Oct 2017]: The Julia+Tableau tutorial blog post is now published.
— Alexander Loth (@xlth) June 1, 2017