Here comes Day 2 of the dashboard week!

Introduction

Today, we are provided with a dataset about CPUs and GPUs that have been released over the last 20 years. We are missioned to visualize the evolution of technology developments with CPU and GPU. We also need to create a user functionality to help users choose what CPU and GPU are suitable for their needs.

As we need to make presentations for the dashboard we made on Day 1, we only get to start today’s project from 10:40am.

Step 1 (Morning 10:40am – 11:40am)

We got a new dataset about CPU and GPU development over the years. This dataset involves a lot of technical terms about the specs of a CPU or GPU product. After initial exploration of the data, I know I need to understand the fields.

I spent 1 hour of time watching Youtube videos and asking ChatGPT to help me understand those terms and understand CPU & GPU in general. This is important when it comes to story-telling. I need to know the content of the analysis well enough to give a good presentation.

Step 2 (Morning 11:40am – 12:30pm)

I started exploring the data in Alteryx and cleaned the data. Then I exported hyper file and started making charts in Tableau. I started off making a bunch of charts, but soon I am thinking about the purpose of my dashboard. I need my dashboard to be useful in some way, not just showing trends. That lead me to think about user perspectives and UI design. I then come up with the idea of helping people to choose what CPU and GPU to buy based on specific needs.

I started drawing my UI design to visualize how I want my dashboard to look like.

Again, relax and have your lunch! I had a bit more rest today:)

Step 3 (Afternoon 2:00pm – 5:00pm)

I started builting the charts I needed. While building charts is quick, formatting consumes a huge amount of time. As I planned to have multiple dashboard pages, I am only around 70% complete at 5:00pm.

After another 2 hours extra work at home. Job is done. But it’s all worth it. Loving my own dashboard 🙂

 

The Data School
Author: The Data School