Phew, last day? Last challenge?! Wow – we’ve (nearly) made it!

And it’s certainly been an intense week with some very tight deadlines in which to manage a lot of data wrangling and creative building in Tableau, but I’ve certainly learnt some new tricks!

First up though; we had one more snug deadline to get through. Our final challenge was made 9am that morning – to be explored, prepped and presented by 3pm the same day (plus blog!).

The Dataset

Today’s challenge data was the dataset that our incoming colleges the DSAU10’s used in their application to the Data School. Which is the Iowa Liquor Sales.

While not much of a drinker myself, this dataset had a lot of interesting information that could be displayed in a number of ways, and I may explore it again with a little more time to do so. But for today, speed is key.

Quick Check and Prep

Although it looked like a fairly tidy dataset, after I fired up Alteryx I found a few things I wanted to improve. I converted a date, added county populations, split and repopulated the Store Names and Cities, before converting latitude and longitude coordinates into usable geospatial points.

Then onward (and back) to Tableau!

The Final Adventure

I wanted to finish the week with a simple story focus that I could build upon. In the end, I came with the following scenario;

Let’s say you’ve just touched down from a busy airport in Iowa (so more possibly pre- or post-covid). You’ve had a long day, your feet are killing you, and you just want to get to where you are staying, have a drink to wind down and crash for the night. Which Stores are within a range you, or the taxi, can reach. Do they even sell the brand of liquor you want? You don’t want to make the trek for nothing!

A quick search revealed that the Des Moines International Airport is one of two of Iowa’s busiest airports. That seemed like a likely location a travel would come through, so I selected this Airport as my ‘touch-down’ site. Using a Calculated Join, I attached the latitude and longitude for the Airport to my dataset in Tableau.

Then I created distance lines between the coordinates I made in Alteryx and the Airport.

Built a parameter to change the distance in kilometre, and a bar chart showing all the alcohol varieties in the Stores within that range and presto!

Additional improvements with a little more time? Well, it might be fun to add additional Airports to ‘arrive from’. So that you can touch down anywhere in Iowa and see the nearest Store that stocks your preferred brand of alcohol.

In Conclusion

For the time I had, I’m quite pleased with my final dashboard and definitely pleased to have successfully navigated all the challenges of Dashboard week!


Tamara Allcock
Author: Tamara Allcock

Tamara has an interesting background in veterinary science, data analytics and retail. She discovered her passion for analytics while working on a range of research projects involving Australian and exotic wildlife. She was excited to learn about the Data School and the opportunities it provided to develop this interest into a career path. It may be a common preference, but she thinks you can’t go wrong the variety of options a delicious pizza offers. In her spare time, Tamara is an avid reader and watcher of fantasy, science-fiction or assorted pop culture and also enjoys painting, craft projects and writing.