(Photo by Christina Morillo)
It was not what I planned. Waiting for the datasets for my first real-world data science project, my impatience grew to the point that I couldn't do nothing. So, I started to lay out the plans. Thanks to my current job, I had a good understanding of the type of the data I would work on. I detailed required data cleaning, possible analyses, how to visualize the outcomes, and terms to define for the project.
Once I received the big and fat datasets, I learned that planning ahead was the right thing to do. It allowed me to:
- be less overwhelmed by the dataset.
- have a check-point where I make sure to have a firm understanding of the project--its purpose and the main question--before hastily putting my hands on the computer keyboard.
- spot unexpected trends and pose interesting questions because I start the project with some expectations.
So, start the data science project without the data. Draw out plans not to be constrained by them, but to be productive, flexible, and exploratory. Now I'm close to the end of the first project and already started to make plans for the next project.
This time, not out of impatience, but out of excitement.