TIPS I WISH I KNEW BEFORE
Starting A Data Career
Take Note of These Points if You are a Junior Data Analyst
Regardless of working with R, Python, Excel or PowerBi, somethings stay the same, you need to clean data. This is something that all beginner data analyst should be aware of. Making data models, machine learning models, and graphs, are part of the job, but really as the maxim goes, it’s only 20% of the job. The 80% really is data cleaning.
Furthermore, most managers don’t understand that data analysis involves a lot of data cleaning, unless they are data analysts themselves. In my experience, managers believe that a data analyst should be able to craft whatever graphic they want in a matter in minutes like an artist painting a portrait on demand. However, they tend to neglect the fact that most business data is messy.
Nevertheless, data analysts are like artists in some ways, but instead of mixing painting and performing the right stroke, they cleanse data. It’s not really beautiful and can be a bit mundane. Furthermore, artists sometimes take hours to years to paint as well.
Here are some tips, I’ve gathered over the years that are transferable between languages and platforms, and which can help you become a better data cleaner. (Yes, not a data analyst)
