With the answers

Spotify Interests; Tableau Public

Yes, I am controversial and included R. Kelly. Just thought the emojis were outrageous.

Key Takeaway 3: Passion trumps years of experience.

For Skyler, doing something he was passionate about helped him land his dream job at Spotify. Skyler loves music. Skyler told amazing data stories on his own time using the publicly available Spotify API. Eventually Spotify took him in-house as an employee. He begins his presentation by mentioning he has only been using Tableau for three years. Yet he has some of the most popular data visualizations on the Tableau Public platform.

Home Depot

Presenter: David Berry | Leader of Business Intelligence & Chase Zieman | Leader of Analytics and Data Science

Award for Best Simultaneous Use of Prescriptive Analytics & Puns

YouTube Views: 307 | Time: 57 minutes (with QA)

Not Tooling Around; YouTube

Key Takeaway 1: A great way to enhance a business relationship or feedback loop is through a dashboard.

Home Depot owns a company called Blinds.com. Blinds.com does not actually manufacture the blinds. They use numerous vendors for their product. In order to have a better relationship and feedback loop they provide a Tableau dashboard to their vendors.

One takeaway here is that they mentioned their vendors aren’t always the most tech savvy. They intentionally designed their Tableau dashboard as something that can be easily pushed to a static PDF and shared more like a traditional scorecard. Obviously being able to interact with a living dashboard is preferred, however, it cannot always be expected that the audience will engage with a dashboard in that manner.

Key Takeaway 2: If you have a website you should be modeling off your click stream data.

Blinds.com bridges this data set with everything they already know about the customer. The algorithms are able to point out and uncover improvement opportunities for the website, customer experience, or if the customer might just be prone to making mistakes themselves.

Key Takeaway 3: At the end of the day judge a model not by its accuracy, but by its impact to the company.

When the algorithm picks up orders to review, orders that are predicted to have issues, it ranks them by expected cost to the business.

Chase mentioned there are so many different KPIs you can judge a model by, but the most important thing the model can do is reduce costs and help the company do better — so they judge their models by the reorder probability multiplied by expected reorder cost. This gives them an actionable metric that the business can leverage.

Conclusion

These were my three favorite and most time worthy sessions. I wanted to go ahead and drop the link so if want, you can explore the remaining 436 sessions.

Tableau Conference 2018 Session Library

Also since I watched a bunch of these videos I wanted to share some other company sessions that were considered but didn’t make the cut (yet still worthy of a fake award)

Didn’t Make the Cut Awards:

Johnson & Johnson | Award for Best Implementation of a Tired, “We’re Better than Excel Spreadsheets” story

Google — Nest | Award for the Session Everyone Wishes was Recorded, but Wasn’t

Facebook | Award for 1st place in the “I Came to be Impressed but Instead I was Shown Slides of Urinals” Contest (they were the only one to compete)

Boeing | Award for the Most Simultaneously Beautiful and Ugly Dashboard

Alberta Health | Award for the Most Vigorous Use of the Stop Light Color Scheme

Run Disney | Award for the Most Beautiful Deep Dive into Mediocre Data

Portland Trail Blazers | Award for Implementing Team Colors into Every Viz Possible