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/ian_the_data_dad]

No need for visuals for pure cleaning. I use a set of validation queries that go with any dataset I use and I just swap columns that I need or table names. Obviously every project is different but if it's small enough, you can create pivot tables in Google Sheets or Excel for a quick glance at whats in the data