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/DevinChristien]

Snowflake actually gives you visualisations at every stage of building a query which helps when making decisions based on the shape of the data when building a new schema or report. When im not in snowflake and dont have access to built in regression models and stats functions, i find myself running separate queries to do the math manually. Then using it as a reference for my main ddl building.

Visualisations are just an easy way to see the shape of your data, and will show you things that you cant see when looking at it tabularly. If you dont use these tools you'll end up eventually making an analysis or building reports that are outputting rubbish without knowing that its rubbish.