What did I gain from Tableau Conference 2017

While on my flight back from Las Vegas after attending the most vibrant, awesome, huge Tableau Conference 2017, I decided to do a writeup on my experience as a first timer attending this conference. And I started drafting all the points that I wanted to say. Just as overwhelming the conference was, even the points that I wanted to document in this post were also so overwhelming and I was so confused how to pick those top 5 or 10 points that resonate in my mind. I have to acknowledge that writing is definitely NOT my skill. So no wonder, my situation was like a little girl lost in the candy land to choose those top points….....

And then slowly, I started seeing some awesome blogposts sharing their experiences at the Tableau Conference. And after reading each of those blogs, I felt this is exactly what I wanted to write. Here are some great blogposts that I really loved reading them –

So what are the 3 points that are unique from my experience gained from Tableau Conference? 

1. The moments when I met in persons some my most admiring Zen Masters, Tableau Ambassadors, and Awesome Viz-ards from the Tableau Community. These are people who inspried me to build my data vizzing skill. 

2. The moment what I came to know that one of the Data Vizzes that I made based on the inspiration from "Devs On Stage" was choosed as the Viz Of the Day and is now added to the Gallary of Vizzes. And Devs On Stage team tweeting about the viz. 

<blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">Awesome job <a href="https://twitter.com/pavanid?ref_src=twsrc%5Etfw">@pavanid</a> ! <a href="https://twitter.com/hashtag/tableau?src=hash&amp;ref_src=twsrc%5Etfw">#tableau</a> <a href="https://twitter.com/hashtag/vizoftheday?src=hash&amp;ref_src=twsrc%5Etfw">#vizoftheday</a> <a href="https://twitter.com/hashtag/data17?src=hash&amp;ref_src=twsrc%5Etfw">#data17</a><a href="https://t.co/SJTF3CCTBl">https://t.co/SJTF3CCTBl</a> <a href="https://t.co/sm78wkvS3o">pic.twitter.com/sm78wkvS3o</a></p>&mdash; Marcelo Guerra Hahn (@marceguerra) <a href="https://twitter.com/marceguerra/status/920409386165575680?ref_src=twsrc%5Etfw">October 17, 2017</a></blockquote>

<script async src="//platform.twitter.com/widgets.js" charset="utf-8"></script>

<blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr"><a href="https://twitter.com/pavanid?ref_src=twsrc%5Etfw">@pavanid</a> awesome, very cool. I am feeling the post TC blues as well.    <a href="https://twitter.com/marceguerra?ref_src=twsrc%5Etfw">@marceguerra</a> when do you plan to share the fractional cow trick. <a href="https://t.co/W3lpSXQuYG">https://t.co/W3lpSXQuYG</a></p>&mdash; Neelesh Kamkolkar (@neeleshkamkol) <a href="https://twitter.com/neeleshkamkol/status/920453917028204544?ref_src=twsrc%5Etfw">October 18, 2017</a></blockquote>

<script async src="//platform.twitter.com/widgets.js" charset="utf-8"></script>

<blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">This is awesome</p>&mdash; Shahaf N (@msshahaf) <a href="https://twitter.com/msshahaf/status/920676914674638848?ref_src=twsrc%5Etfw">October 18, 2017</a></blockquote>

<script async src="//platform.twitter.com/widgets.js" charset="utf-8"></script>

<blockquote class="twitter-tweet" data-lang="en"><p lang="in" dir="ltr">Terri-bull.</p>&mdash; Kent Marten (@datakmart) <a href="https://twitter.com/datakmart/status/920510558394253312?ref_src=twsrc%5Etfw">October 18, 2017</a></blockquote>

<script async src="//platform.twitter.com/widgets.js" charset="utf-8"></script>

3. 

1.       Michael Mixon post – Introversion 2.0 resonates so much as I feel – every line of what he said from an introvert mindset.

2.       Mark Edwards post – Reflections on a firstTableau conference – Another great recap of the conference. As Mark says in the post, the hardest part is to put in words about experience you get attending Tableau experience.

3.       Sarah’s post – What happens in Vegas….. #Data 17

And then slowly, I started seeing some awesome blogposts sharing their experiences at Tableau Conference. A

So what else do I have to share that is very unique to me?

However, I proudly share what I gained in the Tableau Community. One of the data vizzes that I have done based on the inspiration from “Devs on Stage” was recognized as Viz of the Day on 10/17/2017.

https://twitter.com/marceguerra/status/920409386165575680

Python Links

Pandas iloc, loc and ix examples

Dumbbell / DNA / Barbell charts - Slight variations and different story telling

Today I was reading about Ryan Sleepers tutorial on how to create Dumbbell charts. Coincidentally, an article popped up today on my twitter feed about "Why are US Presidential Elections So Close?" published by nautilus.com. Obviously what caught my attention is not the article itself but the chart that was put in the article.


The chart basically shows the % of popular votes between two prominent US political parties - Dems and Reps in the last 48 election seasons (ie from 1824 till 2012). The chart clearly articulates the subject of the topic - how big is the gap in the % of popular votes during each political season and clearly identifying where each party stands. Looking at the top circle tells us which party was the most favorite and the line joining the bubble gives a sense how wide the gap is between the parties. Simple yet very clear story.

Coincidentally, I have been reading a number of blogs on how to create dumbell / DNA / Barbell charts from here, here and here. With this triggering points, I thought why not I write my learnings about how to use charts with slight variations to tell variety of stories.....And thus led me to writing this blogspot.

Technically the charts look the same but the making is very different based on how the measures are used. The workbook at the end of this post,  shows some variations of how a dumbbell chart is created in 2 scenarios -

1. When multiple measures are used - Corporate Sales and Home Office Sales
2. When same measure but cut by a dimension is used - Ex - Sales cut by Segment

It also depicts two of the use cases where they are apt to showcase -

1. Show how wide the gap is between the metrics - The following demonstrates how wide the gap is between the Home Office and Corproate Sales (Similar use case as what the Nautilus.com shown here). The charts are built based on the type of measures(single or multiple measures) used - 





2. Show how the sales changes period over period across the dimension - Below  chart shows how the sales have been YoY between two comparison years. 



Self learning tip - Get to be bottom of Table calculations - what, why, how, where etc.....They are such a powerful calculations that if used smartly, we can do wonders with our vizzes. :)

Now moving on my next topic of Viz learnings.....

HDMO - Happy Data Make Over :)