Build a Voronoi Treemap in Tableau in two steps

tl;dr
1.
Use this Observable Notebook to input your data and download the CSV result file.
2. Download this Tableau Template and refresh the extract with the downloaded file.

Introduction

A few weeks ago, I discovered that you can convert any SVG element into a polygon. This means that you can convert any crazy visualization generated by web libraries, like d3.js, into a simple list of X and Y coordinates, perfect to use in Tableau. Quite exciting, right? If you are not excited by this, I am for both of us.

Almost at the same time, I came across the beautiful work of Victoria Rose. And where most people will only see wonderful mini field aerial landscape, it also reminded me of a Voronoi Treemap, and Frank Lebeau’s work to generate them using d3.js.

Combining the two ideas, my goal was first to find a way to easily create Voronoi Treemap in Tableau, and showcase it in a Land Cover visualization. As for the Network Graph, the main challenge was to make the solution easy to use for everyone.

After some time, the solution was ready and I was able to quickly build this visualization, in Tableau:

But if you’re here it’s probably because you want to build something like that too, right? Then let’s not make you wait any longer, all you need is a CSV file!

Get the data

Contrary to the Network Graph generator, you don’t need a special data structure to create a Voronoi Treemap.

All you need is a CSV file with a least one dimension and one numeric field. The separator doesn’t matter as you’ll be able to define it yourself (by default, the comma is preferred).

In the rest of the tutorial, I’ll use the Sample – Superstore CSV file. You can download it here if you don’t have your own data:

Are you data-ready? Let’s make a Voronoi Treemap!

Step 1: Generate the Voronoi data

Before we start, a huge thanks to Will Chase for letting me fork his Voronoi Treemap Observable example as the starting point for my data generator.

tl;dr
Open this Notebook and replace the existing file with your CSV.
Select one field to Split the Treemap, one for the Size, and optionally one to Group the elements.
Download the voronoi.csv file.

If you read the Network Graph tutorial, you won’t be lost. If you haven’t, the idea is quite simple: use a preconfigured Observable notebook, to generate the initial render and then download the result in a CSV that Tableau can easily understand.

Here’s the notebook we’ll use in this tutorial:

https://observablehq.com/@ladataviz/wip-voronoi-data-generator

The notebook is separated into six parts, but you’ll only use four of them:

  • File: to replace the existing CSV by yours and change the delimiter (if needed)
  • Voronoi: to configure the field to use to render the Voronoi Treemap
  • Download: to get the voronoi.csv file needed for Tableau
  • Result: to visualize the initial render in SVG that will be converted in polygons

Let’s visualize our data.

On the Notebook, start by replacing the existing CSV,CO2@1.csv, by your file. To do that, click on the paperclip that shows up when you hover over the first cell and click on replace:

If your CSV doesn’t use commas as separators, you’ll have to modify the Delimiter input.

For example, the delimiter of the Sample – Superstore CSV is a TAB. In order to use this file, I need to enter \t in the Delimiter input:

To finish the configuration, select at least one field to Split the Treemap and one numeric field used for the Size. Optionally, you can also use a third field to Group the element.

In my example, I use State for the split, Sales for the size, and Region for the group. Here’s my configuration and result:

When you’re happy with the result, use the button, highlighted in the screenshot below, to download the result file: voronoi.csv:

This file contains all the required information to build the graph and use it in Tableau. And that’s exactly what we’ll do in the second and last step!

Step 2: Visualize your data with Tableau

tl;dr
Download this Tableau Workbook Template, open it in Tableau Desktop, and refresh the Voronoi Extract data source with the downloaded file
.

First, download the template, available here. Click on the button at the bottom, highlighted in the screenshot below, then click on « Tableau Workbook » and finally choose your Tableau version:

Open the file in Tableau Desktop and refresh the Voronoi Extract data source, as highlighted in the following screenshot:

You’ll get prompted that there is a problem and Tableau can’t find the file. That’s normal because Tableaus is trying to find it in its previous location, my computer.
Click on Yes to edit the connection:

You are redirected to the Data Source page. Here, you’ll see that the voronoi table is red. To edit the connection, click on the small arrow next to the voronoi connection and select « Edit Connection… »:

On the window that opens, search for your downloaded voronoi.csv file, and open it. You should now see the data sample, indicating that everything is working fine:

Finally, click on the Dashboard, « Voronoi Treemap Template« , at the bottom, to go back to the visualization. You should now see the two pre-configured Voronoi Treemap, in Tableau, with your data:

The Voronoi Treemap template offers two versions: one where the color is on the Value and one where the color is on the Group. By default, the labels are displayed for the segment where the value is higher than 6%, you can change that by editing the X for text field.

Note: If you haven’t selected a group in the configuration part during step one, you can also replace the color from Group to Split to have a different color for each dimension, as I did in the Land of Color visualization.

Of course, this is only the starting point and you should be able to easily change the colors, border, background, font, and add any interaction you may need! Have fun!

Wrap-up

Thank you for reading this new tutorial!

The same technique can be used to generate any kind of custom visualization, so if you have any requests, feel free to ask!

Of course, if you face any issue with this solution or have ideas on how to improve it, I’m more than happy to learn from you.

Tristan / @ladataviz

Build a Network Graph in Tableau in three steps

tl;dr
1. Get or create a JSON file with nodes and links structure like explained here by Yan Holtz.
2.
Use this Observable Notebook to input your JSON and download the two CSV files.
3. Download this Tableau Template and refresh the extract with the downloaded files.

Introduction

Hello #datafam!

Recently, I’ve created my first data visualization using d3.js and canvas. The idea was to visualize the tweets and mentions during the last Tableau Conference. Quickly, I realized that I could use the data generated by d3 and simply plot the result in my favorite tool, Tableau. Here’s the result:

Then, the idea was to simplify as much as possible the steps to transform any network dataset into a Tableau visualization. Hopefully, this goal was achieved, but I let you be the judge after you finish this tutorial!

The main idea is to use the d3.js force layout to generate the initial layout and download generated the data (don’t be afraid, you don’t need to learn to code!). Then, use this data to feed a Tableau template with everything ready and pre-configured.

Ready? Then let’s start with step 1, finding a dataset to visualize!

Step 1: Find/Create a network dataset

tl;dr
You need a JSON file with appropriate structures, containing nodes (with id fields) and links (with source and target fields) like explained here.
You can search for examples
here.

The first step is to find (or build) a dataset, in JSON format, with the appropriate structure. This structure is composed of two main elements:
nodes: with required id fields
links: with required source and target fields

Here’s an example:

{ 
 "nodes": [
    { "id": A },
    { "id": B }
  ],
  "links": [
    { "source": A, "target": B }
  ]
}

By searching network on Observable, you’ll find many examples with attached files.

If you already have your data, but in a different format, you can use this great resource from Yan Holtz to reshape your data. Of course, you can also use any other data preparation tool, as long as the output is similar to the one described above.

For the rest of the tutorial, I’ll use this file. It comes from this project and shows similarities to songs according to last.fm.

As you can see the file contains our required format: nodes with id and links with source and target. All the other fields (like match or name here are not required but will be available in Tableau).

Once you have the file ready, it’s time to generate the data and let d3.js do its magic.

Step 2: Generate the data

tl;dr
Open this Notebook and replace the existing file with your
JSON.
Play with the Config part to change the layout.
Download the two CSV files.

As explained in the introduction, we’ll use d3’s Force Layout to generate the data. But how can I do this, without knowing d3.js or even Javascript? you may ask.

The answer is ObservableThe magic notebook for visualization
More specifically this notebook (which surely can be enhanced if anyone has suggestions):

https://observablehq.com/@ladataviz/network-data-generator

The notebook is separated into four parts:

  • The most important part, above the graph where you can input your file and download the data.
  • The graph itself.
  • The Config part where you can play with the size of the nodes and the strength of the force. This will change the render of the graph.
  • The Code part (that you don’t need to look at if you don’t want to).

To input your file, click on the paperclip that shows up when you hover over the first cell defining the data and click on replace:

Once you’ve selected and replaced the existing file, you should see the updated graph with your data (in my case, the songs similarity data). You can play with the Config pane to change the strength of the size of the nodes. Here’s my final result:

When you’re happy with the result, use the two buttons at the top to download the two CSV files: nodes.csv and links.csv:

Those files contain all the coordinates and information needed to render the same graph in Tableau.

For the last step, you can use the quick and easy version, using a pre-configured template, or find, below, a more detailed version where we’ll build the graph together from scratch.

It is now time to open Tableau and visualize our data with our favorite tool!

Step 3: Visualize your data with Tableau
(quick version with template)

tl;dr
Download this Tableau Workbook Template, open it in Tableau Desktop, and refresh the Extract Data Source with the downloaded file
s.

You choose the quick and easy version, that’s perfect to get your network graph working in Tableau in less than five minutes!

First, download the template available here. Click on the button at the bottom (highlighted in the screenshot below), then click on « Tableau Workbook » and finally choose your Tableau version (2019.2 minimum if you want all the features):

Open the file in Tableau Desktop and refresh the Network Graph Extract:

You’ll get prompted that there is a problem and Tableau can’t find the files. That’s normal because Tableaus is trying to find them in their previous location, my computer.
Click on Yes to edit the connection:

You are redirected to the Data Source page. Here, you’ll see that all the tables are red. To edit the connections, click on the small arrow next to nodes and select « Edit Connection… »:

On the window that opens, search for your downloaded CSV files, and double-click on nodes.csv. You should now see the data sample, indicating that everything is working fine:

Click on the Dashboard, « Simple Network Graph« , at the bottom, to go back to the visualization and voilà, here’s your network graph, in Tableau:

There are already some built-in features in the template like the node and links highlight when you click on one of them (only available from version 2019.2).

That’s it! Feel free now to modify this template, change the colors, layout, size, add information, interactions, and anything you want to create the next VOTD!

If you want to learn more about how this template was built, read the next section.

Step 3: Visualize your data with Tableau
(step by step version from scratch)

Oh! You’re here for some challenge and you want to learn how to build a network graph, congratulations! Let’s not make you wait any longer, and open Tableau!

Create a new Text file connection and select the first file: nodes.csv. You’ll probably get the same error as me: Tableau doesn’t understand the file format immediately. To correct this issue, click on the Text File Properties option, and make sure it’s configured like in the picture below:

Note: you may have to select something else than « Comma » then « Comma » again.

Then, drag and drop the file links.csv from the left pane next to the existing nodes.csv and repeat the same operations to configure the text file properties.
One it’s done, you can create the left join between nodes and links on the id field.

You need a left join as they may be nodes without links

Your data source is ready, we can start building the viz.

On a new worksheet, put x and y (from the nodes table) in respectively columns and rows. By default, Tableau will aggregate the values because the fields are listed as Measures. You can either convert them to Dimension in the Data Source (and then, convert them again to Continuous) or right-click on the pill and select « Dimension« :

Change the Marks type to Circle. Here are our nodes;

Now, drag and drop x coming from the links table next to existing x in Columns. Make sure you’re also using the pill as a Continuous Dimension, and change the Marks type of this x to Line:

Then, drag the key field, as a Dimension again, on Detail. Here are our links:

Finally, click on the second axis and select Dual Axis:

Don’t forget to synchronize the axis and, if you want the same layout as in Observable, reverse the scale of the y-axis. Change the format (hide the header and remove the grid and zero lines) and you are done:

Wrap-up

Hopefully, with this tutorial and tool, you are now able to easily visualize your network data in Tableau!

Don’t hesitate to leave a comment if you think this method can be improved. I’ll also create an additional blog post explaining how to work with data-driven nodes sizes.

Thank you for reading!

Tristan / @ladataviz

Build and deploy a Tableau Extension with React, Git, and Netlify

In this first technical blog post, I’ll do my best to take you through the steps to create, build and deploy a Tableau Extension using Git, React, and Netlify.

Before we start, you should know that Javascript, React and, in general, web development is not my main skill. I’m a Data Visualization Engineer, and I spend much more time building dashboard rather than web applications.

However, I was encouraged to write this article to help other beginners. Indeed, if I was able to do it, you can surely do it too! Let’s start!

Our goal and why this tutorial

The goal of this tutorial is to set up a very basic Extension, that just says « Hello » plus the name of the current dashboard:

Yes, I agree, it’s not very useful. However, we’re going to use three of the current most exciting technology:

  • React: a component-based and feature-oriented JavaScript library for building user interfaces
  • GitHub: the leading version control management tool
  • Netlify: a free and super easy hosting and deployment service that you can link to GitHub

With those technologies, you’ll be able to

  • Develop powerful extensions (and use the Tableau UI API)
  • Have your code safe, secured, and versioned
  • Be able to work with other developers easily
  • Make the extensions available to the world
  • Have continuous deployement (meaning that you just have to push new features, and everyone will see the modifications)

If that sounds good, let’s start!

Initialize your React App

As we’ll build our Extension using React, the first step is to initialize a React application.

To do that, you need to first install Node. You can download and install it here: https://nodejs.org/en/.

Then, open a Terminal, navigate to a folder where you want to initialize your React app, and write the following command:

npx create-react-app hello_world_extensions_tutorial

This will install and initialize a default React application name hello_world_extensions_tutorial.
Navigate to the newly created folder and start the application:

cd hello_world_extensions_tutorial
yarn start

Once all the scripts have loaded, a web browser page will automatically open and display the default React init page:

Our React app is working, the next step is to publish and synchronize it with GitHub.

Sync with Github

The React application already is already initialized to use git. The only thing we have to do is create the repository on GitHub and link it to our React app.

Go to https://github.com/, log in (or create an account if you don’t have one) and create a new repository. Name the new repository hello_world_extensions_tutorial.

On the quick setup, we’ll use the « push an existing repository » command lines. In a terminal, navigate to the react app folder create earlier, and copy-paste the two lines (Note: your command lines will be a bit different):

After pushing your code, you should see your entire React app folder in GitHub:

Our default app is on GitHub. The next step is to develop the Extension.

Create our first Extension

Using your favorite code editor (I’m using VS Code) open your hello_world_extensions_tutorial folder.

There are four main steps to build our Extension.

  • Add the Extensions API library in the public folder

You can download the library here:

Unzip the downloaded file and add tableau.extensions.1.3.0.min.js in the public folder.

  • Reference the library in the index.html

In the public folder, open index.html and add the reference of the script under the title:

<script src= »tableau.extensions.1.3.0.min.js »></script>

  • Write the application

The next step is to actually develop the application. To do that, in the src folder, we’ll modify the App.js file.

Note: As the official Tableau tutorial uses class and componentDidMount I choose to use them, but if you are familiar with React Hooks, you can also replace the following code with the one here: https://github.com/ladataviz/hello_world_extensions_tutorial/blob/master/src/AppWithHooks.js.,

Here’s the code that returns « Hello  » + the dashboard name:

import React from "react";
require("./App.css");

//Needed to use the library
const { tableau } = window;

//Initialize the class and state
class AppComponent extends React.Component {
  constructor(props) {
    super(props);
    this.state = { dashboardName: "" };
  }

  //Update the state by passing the dashboard name
  componentDidMount() {
    tableau.extensions.initializeAsync().then(() => {
      const dashboardName = tableau.extensions.dashboardContent.dashboard.name;
      this.setState({
        dashboardName
      });
    });
  }

  //Render the Title
  render() {
    return <h1> Hello {this.state.dashboardName}</h1>;
  }
}

export default AppComponent;

You can copy-paste the code in the App.js file. I won’t go into the details of building an Extension in this post. You can find tutorials, get started, and API reference here: https://tableau.github.io/extensions-api/

  • Create the .trex manifest

The .trex manifest is the description of the Extension. The most important part is the url in the source-location where we define where the code is running. To test our application, the URL we need to specify is our local environment:
http://localhost:3000/index.html

At the root of the application folder, create a new file, Tutorial Local.trex, and write the following code:

<?xml version="1.0" encoding="utf-8"?> 
<manifest manifest-version="0.1" xmlns="http://www.tableau.com/xml/extension_manifest">
  <dashboard-extension id="com.ladataviz.tutorial" extension-version="0.1.0">
    <default-locale>en_US</default-locale>
    <name resource-id="name"/>
    <description>Tutorial (React)</description>
    <author name="Tristan Guillevin" email="contact@ladataviz.com" organization="/" website="https://ladataviz.com"/>
    <min-api-version>1.0</min-api-version>
    <source-location>
      <url>http://localhost:3000/index.html</url> 
    </source-location>
        <icon></icon>
  </dashboard-extension>
  <resources>
    <resource id="name">
      <text locale="en_US">Tutorial</text>
    </resource>
  </resources>
</manifest>

You can modify the author and dashboard-extensions id fields.

The code of the Extensions is done, let’s see if it is working.

Test your app!

Run the application. Like before, open a terminal, navigate to the folder of the React app and start it:

cd hello_world_extensions_tutorial
yarn start

Open Tableau, create a simple Dashboard, name it Test, add an Extension and select the Tutorial Local .trex file. You should see this:

If you don’t, make that your React app is running in a terminal on http://localhost:3000/index.html (open this URL in a browser, you should see « Hello ») and that the code is similar to the one in my Git repository: https://github.com/ladataviz/hello_world_extensions_tutorial

If your Extension is working fine, let’s update the GitHub repository.

Push your changes

The first step is to push our modifications on GitHub. But first, you can check what modifications are ready to be pushed. To do that type git status on a terminal, in the application folder:

As you can see, there are two modified files (public/index.html and src/App.js) and two new files (the .trex manifest and the API library).

To push our changes we first need to add the changes in git, then commit them and finally push them in our master branch. Run the three following commands:

Git add . 
Git commit -m « Hello World Tutorial »
Git push 

On GitHub, you should see the description « Hello World Tutorial » next to the public, src folders and the .trex manifest:

Our GitHub repository is up to date. The next step is to deploy our application online so everyone can use it.

Deploy your application

To deploy the application, we’re using Netlify.

Start by logging in to app.netlify.com with your GitHub account. Then, click on New Site from Git to start configuring the deployment. The first step is to select the Git provider, we’re using GitHub:

The second step is to give Netlify access to your GitHub repository. First, you need to authorize the Netlify application on your GitHub account. This should be easy. Then, you need to authorize Netlify to access your repository hello_world_extensions_tutorial:

Finally, you can select in from the Netlify app:

The last step is to configure the build settings. Normally you have nothing to change, but make sure that the build command is yarn build and the publish directly is build/. Finally, you can click on Deploy:

Wait for the deployment of the site, and when all is green in the Overview, your site is deployed and ready. You can copy-paste the link of your site in a new web page to test it, it should say « Hello ».

Of course, you may want to modify the name of your site for something friendlier (nostalgic-einstein sounds good but not really representative of what the extensions do!). To do that, click on Site Settings and then Change site name:

Our site should be ready, I named mine helloworldtutorial.netlify.com (you can test it, it says « Hello »). Of course, you’ll need to name it differently!

Our Extension is deployed and available online. The last step is to create a new .trex manifest so you can start sharing your extension to the world.

A new .trex to share

As you know, the .trex manifest is where you describe the extension and reference the URL of the application. If we want to share your extensions, we need to create a new .trex file, referencing our deployed application.

Create a new file, Tutorial.trex and copy-paste the code from Tutorial local.trex in it. Then, you just need to update the url field in source-location to the URL of the deployed application on Netlify. In my case https://helloworldtutorial.netlify.com/index.html:

To make sure it’s working, you can open Tableau and, on a dashboard, select your new Extensions, Tutorial.trex, everything should be working as with the local file.

Anyone who possesses the Tutorial.trex file is now able to use your Extensions.

Your application folder now contains two .trex files. That’s fine as you can use the local one to test the ongoing new features you develop and keep the other one to test the features deployed online.

You can finally push the new .trex file on GitHub so you’ll have a link to share with people (https://github.com/ladataviz/hello_world_extensions_tutorial)

Wrap up

I hope you found this tutorial helpful. Sorry for the mistakes! Don’t hesitate to add comments so I can improve it!

Tristan

#DATA19 Wrap-up and late night thoughts

There are many reasons why Tableau Conferences are amazing: the keynote, sessions, IronViz competition, Data Night Out… But the very best thing is definitely the people.

That’s why I never regret skipping a session just to hang out and chat.

That’s why I never regret staying too late every night to share drinks.

The sessions are recorded. The time you spend with the people isn’t.

And from all those conversations, I wanted to highlight two things dreams that could really become true one day and one topic that blew my mind.

TUG On Tour

The Tableau User Group is what puts the community together outside of the main conference. TUG leaders from all the different cities are doing an amazing job to find new content, speaker, and business case.

With Marian Eerens (@M_Eerens ) and Eugenia Kis (@talva_cz), we started to think that it would be quite cool to make a Tableau User Group On Tour. Visiting all the nice cities, learning from the different TUG leaders, and having a chance to connect with different communities and cultures.

What do you think?

VizDuo

Because DataDuo is already a thing.

Something I definitely want to do after this Tableau Conference Europe is starting collaborating with more people. The discussions with Amanda Patist (@amanda_patist ) and Ivett Kovacs (@IvettAlexa) convinced me that it’s the right path.

And let’s be honest, once you saw what Ludovic Tavernier (@ltavernier7) and Klaus Schulte (@ProfDrKSchulte) managed to build together, you just want to see more people doing that.

Another community project may be too much. #VizForSocialGood #DataForACause #MakeOverMonday #WorkOutWednesday #ProjectHealthViz #SportsVizSunday #IronQuest #IronViz… That’s quite packed already.

But a bit like with #SWDChallenge, it could consist of monthly challenges to collaborate with someone that could totally blend in existing projects.

Let me you know your thoughts.

Extensions

Thank you for breaking my brain Merlijn Buit (@MerlijnBuit).

Merlijn’s session about Extensions showed me some of the craziest things I’ve seen with Tableau. And it definitely made me wants to learn how to bring even more magic into Tableau.

With two main ideas in mind, I hope to be able to contribute not only on Tableau Public, but also on Git starting very soon!

Thank you #DataFam, see you soon!

Discover, Learn, Compete, and Share – My Tableau Journey

Respectively 2015, 2016, 2017, and 2018

2015 – Discover

September 2015 – A new chapter in my life, I’m starting my professional journey by joining Actinvision as a Data Consultant. There are two reasons why I decided to join them:
– they were a recent and energic start-up focused on data in Strasbourg
– they were the only company in East of France to use Tableau, and the founder, Olivier Catherin, was famous in the community for creating a way to build a Sankey Diagram

After two weeks of intense training on SQL Server, Alteryx and, of course, Tableau, I published my very first visualization on Tableau Public « A small story of music » (in French) and started my first mission as a consultant with the Council of Europe.


2016 – Learn

January 2016 – I’m back on Twitter! Apparently, it’s the place to be to get Tableau news, advice and to share. I started following key people in the Tableau and dataviz network. My first followings were Ben Jones, Andy Kriebel, Andy Kirk, Chris Love, Robert Rouse, Moritz Stefaner, Alberto Cairo, Cole Knaflic, Matt Francis, Steve Wexler, Jeffrey Shaffer,…

With only four original tweets and two Tableau Public vizzes in 2016, I was clearly not the biggest contributor. However, I learned a lot. The number of Community Forum articles and blogs I read and Tableau Public visualization I downloaded and studied was massive. For that, I have to thank you, the Tableau Community. I never thought to find a software-related community so willing to help and share.

Professionally, I also had great challenges and experiences. As my skills in Tableau grew,  I was able to travel to Bordeaux, Lyon, Zurich, Singapore, and Sydney to teach and help clients around the world.


2017 – Compete

May 2017 – My first participation in the new Iron Viz Europe competition with the Beer in Europe visualization. At this time, my only will was to explore new ways of using Tableau. Working for clients is challenging, but often your creativity is limited by corporate design rules (let’s not mention the « Just make a big table, please » requests). Little did I knew that five months later I’ll be on the big stage in Las Vegas.

A funny viz about beer isn’t enough to make it to the Iron Viz final. However, the fallouts were bigger than expected. Tableau selected it as Viz Of the Day, and Eva Murray decided to print it on a gigantic poster for the Exasol bar at Tableau Conference London.

Boosted by this, I decided to start sharing my experience and knowledge in the local Tableau User Group, EuroTUG.

June 2017 – Let’s try the big Iron Viz this time, with Nelson Mandela’s moto in my mind: « I never lose. I either win or learn ». For this feeder, I decided to go wild (as the theme suggested), to focus on the storytelling, and add lots of easter eggs and interactivity. I still find it hard to believe when I take a look at other submissions like Russell Spangler’s one, but the 3rd July 2017, I won my ticket to the Tableau Conference and a spot on the final. My first known competitor, Joshua Milligan, is a Zen Master with thousands of followers (I had not even one hundred). Scary, incredible, but freaking amazing.

October 2017 – A few MakeOverMondays and Tableau Public vizzes later, here I am, at Mandalay Bay, the French outsider who has to tell a story about the US Housing Market in twenty minutes in front of thousands of people at the Iron Viz final, next to Joshua Milligan and Jacob Olsufka.

And then, this happened.

One thousand followers, two local newspapers articles (here and here), and dozens of pictures with strangers after, what should I do now? Share.


2018 – Share

January 2018 – Tableau gave me the opportunity to present a webinar to share the secrets behind building a dashboard in twenty minutes and, the same night, I spoke at the TUGParis.

The first half of the year was punctuated by several other TUG presentation, many tweets (if we compare to the previous years), blog articles, and other events like the Big Data salon in Paris and the CMIT forum.

This year, I also started to meet multiple Tableau Community famous people like David Pires, Annabelle Ricon, Elena Hristozova, and Chloe Tseng.

May 2018 – The first change in my professional life. I decided to quit Actinvision and join Ogury, as a Business Analyst. My role and focuses are entirely different: I’m no longer a consultant, and my job is to use our data to build studies (of course, using Tableau) for our clients. My focuses are on the story-telling, the simplicity, and the user experience.

October 2018 – Since I joined Ogury, I only published one new visualization, my resume, but no blog article, no webinar, no presentation… and yet I’m telling you that it’s the year of sharing! The past five months, I was working on the biggest and most difficult challenge I’ve ever had. It’s a project 100% focused on sharing, and it was finally finished the 1st October 2018.

I give you an appointment next Monday, the 8th October 2018, to discover the result and I hope you’ll enjoy it.

– Tristan Guillevin

Let’s bust some IronViz feeder myths

The IronViz Feeder contest. What a great event!
Like always you can expect the best in terms of creativity and skills. But also, like always, a lot of people won’t participate.. for the wrong reasons.
I participated to two IronViz feeder contests, one with my Beer viz and one with my Safari viz. Today it’s time to share what I learned.
So let’s bust some myths about participating (and maybe even winning) an IronViz Feeder contest!

Myth 1: You need to find a great dataset

It’s very hard to find a great dataset. For the IronViz Feeder, you may even spend more time finding the data than creating your viz. But if the MakeOverMonday project proves us something, it’s that you can always create a great viz, no matter the complexity or size of the dataset. One dimension and one measure is enough to start building something.

You want to see the awesome dataset I found for my winning entry?
It doesn’t exist.

I create my own dasaset by copy-pasting data from tables or pictures I found on different website:

Forest loss from: https://rainforests.mongabay.com/deforestation_percent_change.html

Forest cover from https://kids.mongabay.com/elementary/002.html

Endangered species from http://earthsendangered.com/search-regions3.asp

It was long. It was not perfect. But it worked!

Myth 1 : BUSTED!

Myth 2: You need a great idea to start

Participating to two IronViz feeder contests taught me that your final result will probably be far from your first idea. And that’s a good thing. Tableau is the perfect tool to enhance creativity and to let you build at the same speed as new idea comes. But you’ll only find new ideas in one way: start vizzing.

Back to my Safari viz. The first pitch was: you are a biologist and, in order to complete your training, you are kidnapped and abandoned in the middle of a forest. Based on the data you collected, you need to find in what kind of forest you are and in which country. I even found a beautiful website with all the data in order to do that.

But you know what comes next.. I started to build my viz around forest covers and from sheets to sheets I build a totally different dashboard, with a different story and with different data. But that’s ok. More, that’s good. Your story will create itself, bit by bit, and at the end it will look totally different, but probably even better than what you imagine.

But don’t forget the most important: fill the « Sheet 1 »

Myth 2 : BUSTED!

Myth 3: You need dataprep skills

Having a data preparation tool is great. In my professional work I use Alteryx very frequently. Funny that I’ve never opened Alteryx to create my two entries! Excel was good enough for both.

Of course if you want to create very complicated visualization, Excel will not be sufficient. But trust me, you don’t need to create complicated things to win. Only your Tableau skills matter.

Bar charts, line charts, maps and shapes. Those are the only four (basic) marks type I used. Yes it doesn’t looks like your every day Tableau, but absolutely no data preparation was required. Only tableau tricks, and a few floating elements.

Myth 3 : BUSTED!

Myth 4: You are not good enough

If you are afraid of what people may think about your entry, you clearly don’t know the Tableau community enough!

The only thing you’ll lose if you start participating to the IronViz Feeder contest is the fear of participating to the next.

What you’ll gain on the contrary… Lots of advice, compliments, encouragements, new skills and, I’m sure, a new viz on you Tableau Public page that you’ll be proud of.

And who knows, even if not selected, you viz may have a great story…

Myth 4 : BUSTED!


I hope this post gives you all the confidence you need to participate. Again, you’ll not be disappointed. And if it wasn’t the fear that  slows you down, I hope those few advice will help you to create a viz.

The best of luck!

Tristan

An Iron-Interview

A month ago, I participated in the IronViz competition. Here are some thought and advices for future competitors. This article is a short version with only my answers. But don’t hesitate to look at the full interview with Jacob and Joshua answers.

How did you prepare for the competition?

Tristan: After winning the IronViz Safari feeder, I started to participate in MakeoverMonday (by Eva Murrayand Andy Kriebel). It helped me build a dashboard and a story with new data every week, and sometimes data that I found not interesting. Once I received the Iron Viz dataset, my main goal was to find a story and build a dashboard around it. I had some key things in my mind as I built it: make the story interesting and make sure the public wants to use it. Jade Le Van, my sous-vizzer, helped me during that process with great advice. In Las Vegas, she also helped me to repeat the complete process of creation and speech. She tried to distract me by speaking, playing music or even putting her smartphone flash on my face so I will feel “in condition!”

What was your first thought when you received the dataset

Tristan: “Je suis foutu,” meaning “I’m screwed” in English. How I, a young French, could compete against two Americans with a completely US-centered dataset about home values. But I love data and I love challenges. So I started to use my condition as a force and I built I dashboard with things I could understand, simple and engaging. A dashboard that even I could enjoy using.

Some tricks to share?

Tristan: Repeat. Repeat. Repeat. And definitely use the Pause Auto Updates button! Every drag and drop issues a query and with nine sheets in my dashboard, I couldn’t afford to wait a few seconds after every move. So I hit the pause button and I knew exactly where to put all the dimensions and measures in rows, columns, filters, colors,… After placing all elements, I hit again the play button  and just wait for one query. That was my game changer but there are many more things to gain seconds. It needs a complete article!

Tell us more about the day of the competition, how did you feel on stage?

Tristan: I usually don’t sweat the stage. Lots of people noticed that I was quite zen about it. Truth is I wasn’t afraid about 20-minutes dashboard creation. I repeated a lot and I was confident about finishing it in 20 minutes. The speech part however… If it had been in French I would have probably enjoyed it much more! I spent the day before the competition in my room, repeating the speech. Again and again. A few minutes before being on stage, I was really nervous about that speech. And then Elissa Fink came and told me “Don’t be ashamed of your French accent, we loved it” and voilà, you know the rest!

Would you do something different now that the competition is over?

Tristan: I: came in Vegas Monday afternoon, after a 16 hours long trip. And left Thursday, just after lunch. I missed a lot of people and cool things happening during the TC. IronViz was probably a bit too much in my head. I should have allow me to spend more time enjoying being for the first time in United States with the best community!

Any advice for future competitors?

Tristan: For the feeder, just do it. Even if you think it’s not good enough. Do it. And if you are not selected, ask for advice and start again. Worst case scenario, I just became better in Tableau! If you are selected for the final, enjoy it as much as you can. It’s an awesome event and like Curtis Harris told us a few second before the beginning, something you’ll never forget.

What are your best memories?

Tristan: Winning a competition is great, but you are always alone when you win. Even if there are hundreds of people saying congrats and wanting to take pictures with you, you live it alone. And for me the best moments are always moments that you can share. So being in the green room, all (ironviz contestant, sous vizzers and MCs) equally stressed, equally anxious and a bit lost, all sharing events in your life to try to think about something else.. That was my best memory. Second best was, without doubt, the Data Night Out and our little trip in Vegas with the great David Freifeld!

Iron Viz Green Room

Iron Viz contestants, sous vizzers, and MC’s in the green room
moments before the competition

A new adventure

Dataviz

Data visualization is one of my many passions. I do dataviz for my job (data consultant) and as a hobby. A hobby  that brought me to Las Vegas, where I participate and won the IronViz competition in front of more than 10 000 people. It was my first Tableau Conference, my first time in the US, and it was crazy. 

But I couldn’t have accomplished this alone.

A new adventure

Many people helped me, with their blog, when I started to use Tableau. And they still help me or contribute to my evolution. I learn something new everyday. Thanks to them.

By starting  this blog, I want to give back, to help people who begin in Tableau like I was helped two years ago.

 

Thanks.