I’m an avid football fan, and for the last couple of days, I have been preoccupied with one thought whether or not it is possible to guess if a random player is a goalkeeper, defender or striker just based on their statistics (played minutes, goals, passes). Obviously, I didn’t want to assign labels manually. And it’s where clustering comes into play. One of the fundamental questions here is how are we going to determine the number of clusters? The attempt to answer it lies below.
When I started working with Tableau Server, it was a real pain to understand all ins and outs: how to connect to data, how to optimise it, how to keep the dashboard up to date, etc.
Now, after experience getting to know Tableau, I can offer you a glimpse of tips that can facilitate your data work flow with Tableau.
Data scientists, analysts, product owners, and other people who use and present data struggle to enhance their dashboards, which colour to choose, what kind of plot is the most appropriate, what they should include in the background and a lot more. The pivotal moment here is not to forget that our primary goal is to get your message across in the most effective way.
I wasted a lot of time trying to solve this riddle. In the beginning, I was working in the dark so I started to accumulate all sorts of information from different places. …
An avid data scientist and visualisation engineer , always looking for new knowledge.