Extensions for Tableau

As you probably already know if you have followed some of my content over the past couple of years, I am pretty excited about the release of the Extensions API for Tableau. This blog is an overdue follow up from #TC18, where Tamás Földi and I presented on Extensions, demoing a number of extensions covering both advanced visualization types and capabilities (like write back). This post provides some of my own perspectives on Extensions in Tableau as well as the content presented during TC18, along with some new stuff.

First, my thoughts on extensions…

The Good (really good!):

  • With the implementation of the Extensions API, assuming that it is kept up and continuously improved upon by Tableau, we can now pretty much allow for anything to be done within Tableau. Whether this be to make advanced visualizations simpler, or extend the foundation that Tableau provides. The only limit here is your imagination (although I do have to confess to saying the same thing about building visuals directly within Tableau as well).

  • A lot of blockers we run into within Tableau, are already solved. Extensions allow us to leverage solutions out there which may not be Tableau specific. The work I demonstrated at TC18 shows this, taking advantage of D3 and Semiotic to allow for visualization types which previously required a lot of hacking and trickery within Tableau.

  • The Extensions API feels very “familiar” as it is pretty close to the JavaScript API, thus the learning curve is not as steep if you have used the JavaScript API previously.

  • We have BARELY scratched the surface of what is possible, I am looking forward to what the community comes up with over the next year (see my first point below though).

The Bad:

  • Tableau Public does not currently support Extensions (even though it is on >= 2018.2 version). This is a HUGE blocker for community driven Extension development, iterations and learning. As a comparison, countless demonstrations were done via Tableau Public for the JavaScript API, I myself leveraged these to first learn the JavaScript API and then give back by providing some write ups and demonstrations of my own via Tableau Public. This also allowed Tamás and I do to more experimental work with the API as well, and to share this work publicly. That could all be done with only Tableau Public, no desktop license required. Extensions on Tableau Public will enable exponential jumps in capabilities implemented via open source, community driven development and improvements. This needs to be addressed to enable Extension development and invaluable feedback iterations for developers.

  • All developers (including me) are currently building extensions with their own look and feel. This can and will ultimately lead to a disjointed feeling for end users who may leverage extensions from several different developers on a single Dashboard.

  • Tableau’s extension gallery does not provide a way for developers to monetize extensions, this again leads to developers and vendors coming up with their own solutions for payment. The result of this is that it will be more difficult to leverage this content within your company as getting approval to pay a bunch of different vendors for yearly extension subscriptions will likely be a challenge.

  • It is up to YOU (and your company) to do your own due diligence on any extension(s) you are looking to bring into your environment. You should treat extensions the same as any other application you would introduce into your environment, and assess them for security vulnerabilities, etc. This one is not on Tableau, it is on you to be responsible when evaluating and leveraging extensions.

So… Are they worth it? DEFINITELY! But proceed with caution as one misstep can flip this equation on you in a heartbeat, with significant consequences.

Time to get off my soapbox and show you some content. Here are four extensions I have been able to develop to date. All of these were built in collaboration with Tamás Földi and Abraham Szilagyi of StarSchema, ltd. They all leverage D3 and three of the four also leverage Semiotic by Elijah Meeks, which, via D3, handles pretty much all of the hard work, I simply leverage and extend these technologies into Tableau. Below I give you a one liner about each of the four extensions built as of this post and a small GIF showing some one piece of their functionality. Lastly, but definitely not least, here is my Github repo that has all four trex files for you to use on your own (same one shared at TC18). Note that these hit Github pages sites on my Github as well (so they will not work in situations where you cannot call out to Github from Tableau Desktop and/or Server.


Map Projections (initial version released):

There are examples of using different map projections other than Mercator in Tableau. They involve custom shape files and/or hackery/trickery. Why not make this easier?

 

Hierarchy Charts (initial version released):

The Tableau community, including me, have spent countless hours building and then sharing techniques on how to build these types of charts within Tableau. The approaches often include the need for pre-processing of data and advanced hacking. Why not make this easier?

Network Charts (under development):

I have seen a number of network diagrams in Tableau, most of these require extensive pre-processing of data in things like R or NodeXL. Charts like the Chord diagram have been built completely in Tableau, but contain very advanced and heavy computations. Why not make this easier?

Swarm with Summary (under development):

There is work out there around building things like bee swarm and violin plots in Tableau. Some of the implementations require pre-processing, like this violin plot example by Ben Moss. Also, why not allow for more visual aggregations beyond Tableau’s built-in Box Plot, and make this easier while we are at it?

I hope you find this overview useful and if you have comments and/or features you want to see in the above extensions leave a comment below or ping me on Twitter.

Easy as Pie React + D3 Chord Diagrams in Tableau

Easy as Pie React + D3 Chord Diagrams in Tableau

… We are going to be integrating with and leveraging Nivo, which is self described by Raphaël Benitte (it's creator) as “supercharged React components to easily build dataviz apps, it's built on top of d3.” Nivo is one of many react component libraries that work on top of D3, each are different and bring their own features and focus to their projects. Here are a few more worth checking out (in no particular order):

I am going to assume you know how to leverage create-react-app and npm install to get up and running locally and import all the component libraries you will need. If you have not gone through this install process yet Chris’ blog walks you through some key steps you will need to complete, and Google is of course your best friend here. Here are the commands to run:

  • Create-react-app nivo_int

  • Cd nivo_int

  • Npm install tableau-api

  • Npm install nivo

That is it, if you run npm start at this point, your project will be bundled and rendered locally on your machine... Magic!

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To Animate or Not To Animate

To Animate or Not To Animate

Context

Previously I wrote this post around analyzing the predictions generated by 538 during March Madness each year. At the end of the post, I briefly discuss the possibility of telling the same story using animation in place of vertically scrolling through a static set of charts. I believe that, if used correctly, the ability to animate from one chart to the next can greatly assist the reader in understanding your analysis process. 

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Building towards d3.js “plugins” for Tableau

Building towards d3.js “plugins” for Tableau

This post is a follow up to my Vizception post from a few months back. We are still building off the technique described in detail within that effort. Here we will look at two additional implementations leveraging the capabilities available within d3.js (thank you Mike Bostock!).

The first of the two implementations looks at leveraging d3.js mapping projectionsTamas Foldi and I presented this example during a recent Think Data Thursday. Here we will leverage the referenced d3.js code and adapt it for use with our Tableau integration method. This will allow us to build choropleth maps in Tableau with access to the d3 projection library which provides just a few more options in addition to your standard Web Mercator (the Tableau default).

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Vizception: Viz in a viz & native d3.js integration on Tableau Server

Vizception: Viz in a viz & native d3.js integration on Tableau Server

We wanted to show a real example of how to bring more to Tableau Server without additional hardware or hosting needed. That’s right, no additional server purchase requisition requests needed. There are really too many use cases to count when it comes to this, the details herein are only the tip of the iceberg.

We had a few short discussions and landed on the following example. This includes not only native d3.js integration but also an example of viz in a viz (in a viz) on Tableau Server. As a starting point, we used the twitter network graphs that Keith Helfrich and I recently shared, which were showcased on the Tableau bloglast month.

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The Tableau Conference Network

The Tableau Conference Network

As I embarked on this journey a while back, I had some goals when it came to what I was looking to build. These are summarized in the below bullets.

  • Visualize Twitter network growth in detail using some form of network graph
  • Needed the network graph for each year to be comparable to one another
  • Interactivity against the network graphs was a must
  • Provide a way for the user to view the actual tweets
  • Once Keith and I decided to run parallel with our efforts, we wanted to way to “jump” from one view to the other.

The sections below detail out how I went about trying to achieve each of these goals. Don’t ask me why I gave myself so many of them.

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