It’s been an extremely exciting first week as part of the Data School. We got to practice what we have learned about data cleaning using Tableau prep, going through a series of exercises with the help of some more experienced Data schoolers.
In my previous position and throughout my studies, I cleaned the data either manually or, once I started getting used to python, writing scripts. This led me to leave so many errors in my datasets and forced me to go back to the start whenever I made a mistake. This is why my favorite feature of Tableau prep currently is the ability to visualize my workflow and edit any of the previous steps, whenever I need to!
For example, during the preppin’ data challenge of week 7 of 2023 (https://preppindata.blogspot.com/p/the-challenge-index.html ), I obtained this workflow. While it was already challenging just to successfully reach ‘clean 8’, my output did not match the output provided as guidance in the exercise. Tableau prep really made it simple for me to go through the steps and figure out that I had simply forgotten to filter out some data earlier in the workflow.
It was also helpful to go through exercises step by step with the rest of the cohort; it taught us the different methods each of us used to clean the data, as well as how to efficiently communicate our thoughts.
I’m now looking forward to working with Alteryx as it seems to provide even more functionalities to work with and clean data.