If you’ve been in data long enough, you’ve probably made a few classic mistakes and seen others do the same. Maybe it was building a model without understanding the business context. Or skipping proper data cleaning. Or assuming the data was “good enough.”

What’s one common misstep that you learned the hard way  and now look out for in every project?
If you could give one piece of advice to someone just starting out in data science, analytics, or ML, what would it be?
Your experience could save someone else a lot of time, confusion, or even a failed project.

Let’s pass the torch and help the next wave of data experts grow smarter, faster.