Recently I interviewed with an organization for a data analyst role.
A question was asked What does data mean to you?
What was the purpose of a question like that? Were they looking for data-driven individuals?
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Sign up to join this communityRecently I interviewed with an organization for a data analyst role.
A question was asked What does data mean to you?
What was the purpose of a question like that? Were they looking for data-driven individuals?
What was the purpose of a question like that?
These questions are trying to pull out of you if your are passionate about [insert subject here] in your case data. They wanted someone who is passionate and has an opinion rather than someone who answers "it's just my job I don't really care".
Were they looking for data-driven individuals?
See above they were looking for your to have an opinion and start talking passionately about data and you views. An example where would be maybe talking about privacy and some of the changes to the data laws in the EU.
What was the purpose of a question like that? Were they looking for data-driven individuals?
That's an unknown.
What you did miss is what would have given you the answer to this question right there during the interview.
You didn't ask for clarification. If a question is too broad or you don't fully understand it ask for clarification.
This is simply a discussion starter question that opens up a given topic.
The interviewer asks you to define a core element of a topic area they wish to check your familiarity with. It's typically not about providing an exact match for their internal definition, but to show that you are familiar with the term and have some grasp on it.
In some cases it might also be about how you think about certain topics - are you more a theoretician who defines the word with a set of mathematical lemmas and theorems or are you more a practical person who will lead the discussion towards systems or tools that you are familiar with and that have something to do with the topic at hand etc.
What does data mean to me ?
Data on its own is usually just numbers, held on a system. Data can be interpreted to show truths or facts about a companies performance, but this requires integrity, as statistics can easily creep in to form truths from peoples perceptions.
Data can be used to form charts and trends which can be relayed to a specific audience to create a visual picture of how a company is performing.
That's what data mean to me personally.
I have never actually been asked a question like that for any data analyst role. I'm guessing the hiring manager like rhetoric, and likes to know how their employees think. Your type of answer could show your passion towards working in a an analytical role. There is no correct answer to a question like that. It is more about how you come across, but this is true for any type of interview question anyway.
How to answer the question “What does data mean to you?”
In a Toastmasters public speaking club I was in, we used to practice impromptu talks by pulling a random topic out of a tin can, then we had no more than 2 or 3 seconds to think of what to say before we spoke on that topic for a full 2 minutes.
One trick we used was to structure our talk with some kind of chronology. For instance, if we pulled the topic "lampshades" (and yes, we actually used generic boring topics like "lampshades"). We would talk about the lampshades of the past, the lampshades of the present, and the lampshades of the future.
Now if we applied the same kind of trick to the question you were asked. That means you could have spoken about the role of data in the past (let's say in Roman times, or perhaps in the 1980s. The exact timeframe is your choice), the role of data in the present, and the role of data in the future (or at least your opinion of where that field was going). Or if you prefer, you could have spoken about the role of data from your perspective as a child, your perspective as a college student, and your perspective as a new professional preparing himself to enter the workforce.
What was the purpose of a question like that?
The question was unusual and open-ended.
Unusual questions are more difficult to have prepared answers for. Open-ended questions also tend to reveal a lot about potential candidates.
In other words, they were probably looking for a candidate who could think on his feet, who was articulate, passionate, appreciative of his field, a self-starter, self-motivated (not just from money), curious, knowledgeable, organized in his thinking, and possibly even insightful.
At the same time, they were also looking for any potential red flag. If you ask enough open ended questions, an interviewee could accidentaly betray himself/herself while trying to answer such questions.
Interview questions are not always meant to be literal. Long answers are not always necessary.
The purpose of these questions are to see if
and how
a candidate stands out. If you take a literal interpretation of the question, you might miss the point and talk about data and schema too much.
For example, if you were to look at the question What does data mean to you? differently, you could answer with one word to separate yourself from the pack.
Opportunity.
You could then talk about opportunities you have found in data that was not realized before.
Think about what is important for the organization first. Often, this is not a technical answer, but more about adding value to the organization. Answers that address adding value often blow the mind of the one asking the question.
For example, at one organization, the CEO asked me of my philosophy of IT. I answer with, "IT should not be a cost center but a profit center." I then rattled off some ways the organization could make a profit with its IT infrastructure and personnel while serving the organization better with expertise and opportunity at a minimal cost investment. The CEO handed me a blank check, literally, and told me to make it happen. And so I did.
The organization grew exponentially and began buying large properties in and around Washington D.C. making it one of the most wealthy and most influential organizations in town. We became the go to experts in using technology, expertise, and personnel to create opportunities and capitalize on opportunities. We taught what we learned by doing.