July 24, 2019

Part 2 of Learning Tableau: Practitioner Certified

By Tina Boe

If you’ve been following along with me on this journey through the Zero to Tableau Associate training, you would know all about my experience with Foundations certification. If you have no idea what I’m talking about, go and check out my previous blog post here

All caught up? Good. Now let’s talk about phase two: Practitioner certification. 

Learning the Core

In Data Coach’s Zero to Tableau Associate course, achieving a Practitioner certification includes learning the core components of Tableau. There are 10 learning modules to complete before creating an iteration of your Foundations dashboard for re-submission to your trainer. The skills that I learned during the Practitioner lessons include: data unions, joins & blends, calculated fields, data preparation, table calculations, and parameters. All of this is taught in conjunction with the overarching theme of data visualization best practices. 


After completing all of the Practitioner lessons, and their corresponding practice problems and quizzes, I began looking critically at my Foundations dashboard to brainstorm what improvements I could make using my new skills in Tableau. I thought about the story that was told in my first dashboard in which I was focused on showing the end-user the seasonality of crime in Chicago. With this next edition of the dashboard, while using the same data set, I decided to drill deeper into that same narrative with the added component of trends in the location of the crime.

Iteration and Improvements

In order to keep the plot line of seasonality, I chose to show the break down of cases per season with a bar graph. This highlighted the prior conclusion that crime is higher in the summer months. Each bar on the graph is connected to an action that aggregates a map with a circle plotted for each district of Chicago. 

These circles are sized proportionally to the number of cases it contributes to the total crime rate. Also, each circle has an action connected to it that aggregates the percent of total crime from that district and the top types of crime in that district. All of this is done to give the end-user the ability to click on the district nearest to them and explore how much crime, and what types of crime happen in their area.

 The final visualizations shown on the dashboard are there to take crime over time a little deeper. The box plot shows year over year change (between 2017 and 2018) by primary type of crime. I think this gives the end-user an interesting perspective on which types of crimes are on the rise or fall in their city. The last viz shows trend in cases over the course of 12 months. It is broken out into a line for both 2017 and 2018 so the trend of each year can be easily compared to the other.

Help from the Data Coaches

The final product of my practitioner dashboard was changed and improved several times during its production. After talking with my assigned Data Coach, I was able to improve the story of my dashboard with his expert feedback. I was advised to give more context to the end-user. When you are creating a dashboard, it is often easy to forget that not everyone knows the dataset and the context of your analysis as well as you do. 

It was an interesting challenge to iterate upon an already established dashboard, but support from being able to ask questions of my trainer made it seem easy. Now, on to Advanced Certification! Stay tuned…

Data Coach is our premium analytics training program with one-on-one coaching from renowned experts.

Accelerate and automate your data projects with the phData Toolkit