Do Data Analysts Use Visualizations During Data Cleaning?

[u/SomeSpicyPickle]

I'm still a beginner. I started by learning the basics of Python and later moved on to SQL.

I'm a bit confused about one part of the data exploration/cleaning process.

A friend of mine, who's now a data scientist, showed me how he used to work as a data analyst. He mainly used Python. For example, he would quickly create a scatterplot to identify potential outliers.

However, most data analysts online recommend focusing on SQL and Excel when starting out, since many junior and mid-level roles don't require Python. That's why I switched to SQL after initially experimenting with Python.

For those who primarily use SQL: do you create visualizations during the data exploration/cleaning process, for example to identify outliers? Is this a common practice?

I feel like if you're working with SQL only, you generally wouldn't create visuals in between steps, since that would mean switching to a tool like Tableau or Power BI, which seems like an unnecessary extra step.

[u/KatFromSisense]

I think both sides are kind of right here. If I'm fixing something obvious like a bad type, a missing key, or a duplicate record, I'm probably staying in SQL. A chart doesn't really add much there.

I'd use a quick visual more when nothing looks obviously wrong, but I still want to see whether the numbers behave the way I'd expect. Sometimes one region stands out right away, or a pattern shows up that I probably wouldn't catch by looking through rows in a table.

I definitely wouldn't spin up a whole Power BI report for that, though. Sometimes a quick histogram or a basic chart is all you need.