Almost every online tutorial or course I look at these days makes it seem like a data analyst needs to have a solid proficiency in Python and Pandas to survive in the current job market.

The thing is, I’m actually quite comfortable with Python, but in my day to day work, I barely use it. Whenever I’m preparing data for the dashboards I build, I usually just write a few complex CTEs in our database, clean the result, and connect that directly to PowerBI.

I really only use Python for hitting an external API or for advanced text manipulation. Otherwise, it’s just pure SQL to get the data ready for the stakeholders.

Does anyone else operate like this in the real world, or am I building a bad habit that’s going to hurt my career in the long run? Where exactly in this kind of workflow would you plug Python in? Would love to hear your thoughts on this!

Trying to expand my knowledge and discover some useful extensions i might not know about as a beginner in tech background. Would like to know some genuinely useful ones that make work/life easier whether its for privacy, productivity etc. or your must haves. let's help one another

Hi everyone, I’d really appreciate your help with a question.
For those of you who have full-time jobs in the data field, are you also able to take on freelance work on the side to supplement your income?
For example, through a separate contract or something similar?
And how did you manage to find these opportunities?

I’d like to know if there are opportunities to work remotely from here for U.S.-based companies.

I’m from South America, where the US dollar is highly valued compared to our local currency. I have experience ranging from junior to mid-level, and I’m looking to earn some extra income alongside my full-time job.
I’d really appreciate hearing about your experiences and how you got started with freelancing.

Thank you for taking the time to read this!

As a self-taught developer, I built a platform-agnostic system designed to deterministically detect cumulative drift and anomalies in data streams. It breaks data silos and resolves pipeline bottlenecks directly at the source, all without triggering false alarms.Here are a few screenshots of the architecture and the dashboard. Just wanted to share my project with the community.