WHY ARE DATA ANALYST INTERVIEWS LIKE THIS

[u/Nearby-Cockroach8655]

I’m currently interviewing for data analyst roles (mostly entry level) and every take home task i get is the same. It’s a bunch of tables with masked data, and they all want actionable insights, except i feel there’s never enough information to actually find an actionable insight. you can rarely use domain knowledge as identifiable data is anonymised and they never provide enough historical data to see if differences really matter.

Do other people feel this way or have i gotten the wrong end of the stick, if so any advice would be appreciated.

EDIT: Thanks you for the advice in the comments, I think being curious, documenting my process for the analysis I can do and explaining what data I needed to delve deeper is the way to go.

[u/avxjs]

I don't disagree, but I also don't mind. Because everything is so vague, you can often get away with recommending whatever you want as long as you articulate some reasonable assumptions, lol. Especially for entry level roles.

[u/r_Yellow01 → u/avxjs]

That is so dumb. The entire data analysis is based on asking the right questions in the first place. Sometimes in five different ways.

[u/avxjs → u/r_Yellow01]

Sorry, what is so dumb?

[u/Droughtly → u/avxjs]

A lot of attempts to anonymize data break the observable relationship between data points.

Let's say the data original collected is income, zip code, and birth date.

Let's say that data is anonymized. The income is reduced to tax bracket. The zip code is reduced to the general area and not the full postal code. The birth date is reduced to birth year.

There's a real correlation in success, sport participation and socialization based on your exact date of birth because it determines how developmentally mature you were compards to your school cohort. A classic example of this is hockey players, whose birthdates cluster around the winter for the turn of year cut-off that set them to enter pre-school or kindergarten, and by extension sports programs, developmentally older by almost a full calendar year.

When you're missing this information, you can draw incorrect conclusions where models based on your work fall apart in real life. Say with the income being reduced to tax bracket and zip to general area, the neighborhood to neighborhood data can reveal a trend in school taxes, student income, and ultimate financial outcomes. With it absent, you can look at school a and b in the same city and conclude that one us doing worse because of income when the parents actually cluster closer together when accounting for what end of each tax bracket they cluster to, where the real issue could be students showing up later consistently due to a more circuituous bus route to one school.

In real life, the data has infinite dimensions, and the best analysis comes from accounting for all possible confounding factors.

[u/avxjs → u/Droughtly]

Not sure why you're lecturing me... Was looking for clarification from the person I responded to. I am not an entry level analyst. Like I said, I don't disagree that it is a flawed process. But it is what it is.

[u/Droughtly → u/avxjs]

I wasn't. I was answering your question.

[u/avxjs → u/Droughtly]

No, you weren't. I was asking the person I was replying to if they were calling my comment dumb, or the interview process dumb, because that would inform my response. 

[u/Droughtly → u/avxjs]

Hmm, yes, I was?

You were talking about the specificity of data not mattering, but the arguments. They said it was dumb because the specificity matteres. You asked what was so dumb. I explained why the specificity of data matters.

I used very apolitical and bland examples of ways anonymizing data can do this, rather than specific ones. I don't care who you are, you said something incorrect before, were corrected, and you asked as an argument after their reasoning. Your point seems to boil down to, I'm not the person you addressed specifically. But you didn't make a DM, you posted a comment on reddit, so that's irrelevant.

[u/avxjs → u/Droughtly]

Okay, sure. My initial comment was a bit tongue in cheek, but the point I was trying to make was that in the context of an entry level interview, where you are intentionally given incomplete and anonymized data, it is acceptable to make reasonable assumptions. I wasn't making any comment on general best practices. Like I said, I don't disagree that it's a flawed process.

ETA -- I did not ask for "an argument after their reasoning" I was literally asking if they were calling me dumb, lol.