Data analytics, in general, is a subjective concept. More of a buzzword than an actual real question topic, we’ll be focusing on and defining data analytics in the interview as the questions that interviewers ask to test your abilities of data analytics intuition.

Data analytics is a hard concept to test in interviews. The consequences of the difficulty of testing data analytics have resulted in a consistent non-standardization of the interview process. Simply put, no one really knows how to test for data analytics.

Maybe a theme for all of data science and AI, where the only consistency has been the inconsistency in the interview processes so far.

But there are SOME consistencies in data analytics interviews. They almost always involve a theoretical dataset with a schema or one that’s usually populated with fake data. They’re also expecting you to demonstrate your skill set in one or more parts of the entire data analytics process.

As we mentioned before, data analytics is the process of mining data to product insights for human consumption. Therefore the mining data, the speed of your code writing, the production of the insight to test, and the validation of your data quality after doing all three are all subject areas you might get tested on.

Lastly, there’s also the matter of communicating an insight. Because what’s the point of insight if no one knows about it?

However, we can group how data analytics shows up in the interview process in mainly three different areas:

Analyzing Data for a Take-Home Assignment

This is a fairly common process for most entry-level and mid-level data analysts or data science roles. You’ll receive a dataset and a brief description of the contents of the dataset, and you’ll be required to answer questions or provide insights from the dataset itself.

Example Scenario:

• Given this dataset of visitor events and conversions, please analyze it and present your findings in a report.

Data Analytics Case Study

Case study questions show up mainly in live, in-person interviews. Here, the interviewer will try to assess your analytical abilities by asking a case study question and then potentially asking you to write code or a query to return some metrics or analyze the data to prove a hypothesis in real time.

Sometimes a dataset will not be involved, and the case study will involve just hypothetically discussing various solutions. I’ll mention that these questions are very similar to product metrics questions.

Data analytics is just the umbrella term that involves product analytics as well as marketing analytics, and more.

Example Scenario:

• Given this schema or dataset, write a SQL query or pandas code to showcase if feature X results in higher performance for output Y.

Data Analytics Live Presentation

In conjunction with a take-home assignment, many times, interviewers will ask a candidate to either work on-site or at home and then present their analysis to a panel of employees.

This requires a bit more work on skills related to presentation aspects.

Example Scenario:

Present your insights on the best marketing channels for visitor conversions in a manner that an executive at the company can understand. Then subjugate yourself to a panel of interviewers.

Last Thoughts

Lastly, I want to note that there is a difference between data analytics interview questions and data analyst interviews.

For data analytics interview questions, we’re focusing on how to tackle interview questions that are under the subject of data analytics. While data analyst interviews usually DO include data analytics interview questions in them (I hope), there should be some other types of interview questions in there, too, to cover the spread of the responsibilities of a data analyst.

Here are the average interview question types that a data analyst will receive:

As noted, it is different across various roles of data analysts. But data analytics is a specific kind of interview question that is not only hard to classify for getting survey data - but also hard to answer.