It has taken me eight months to finish this series on achieving data comprehension. This is the third and final installment that explains how I have learned to be a data exploiter. You will need to read the article to find out what that means.
I presented this talk on May 4, 2017 in Austin, TX, at the Tableau customer summit. I want to say thanks to Brenda Akers for asking me to do this because it gave me a chance to share my work from the past few years.
There might be a time when you want to search for something in a dashboard, and this something might come from different fields. For example, you might want to search for someone based on their name OR their email address. A solution to this problem is shown in this article.
This is my second short Tableau data story. The theme is motorcycles and being a data dork. You have to read the article for proof of why I believe I am a naturally born data dork.
Now over 30 years ago, the summer of 1986 was a fun one for me. In this short story, I relate some climate data back to my life, with the focus being on July 31, 1986.
Some stories do not need pictures. This is one of them. I don’t often write them this way, but sometimes the truth must be told without accoutrements and embellishments.
Tableau was used to visualize about eight years of groundwater cleanup data. The total volume of groundwater that was remediated and the total mass of contaminants removed was visualized in Tableau dashboards.