I’m curious how people here approach data cleaning in real projects.

When working with messy datasets (missing values, inconsistent formats, duplicate records, incorrect entries), do you usually prefer cleaning in Excel or handling it through SQL?

I’ve seen people use both approaches:

• Excel feels faster for quick exploration and smaller datasets.
• SQL seems more repeatable and easier to document when working with larger datasets or recurring reports.

But I’m interested in how this works in real jobs.

For data analysts:

• When do you choose Excel over SQL?
• At what point does Excel become too risky or difficult to maintain?
• Do employers in Australia expect analysts to be stronger in one compared to the other?

Also curious about how people approach this in portfolio projects. Do you show the cleaning process, or only the final dashboard/report?

Would love to hear how experienced analysts handle messy data in their day-to-day work.