[0:00]They're just trying to see how the heck do you think, like, what is your thought process? I love that you like pulled out a calculator, and I love that at the beginning how you like asked for clarity. I think that's really important. Welcome to the Data Career podcast, the podcast that helps aspiring data professionals land their next data job. Here's your host, Avery Smith. In this episode, you're going to see me interview two random strangers and ask them data analyst interview questions in hopes of preparing them for their upcoming interviews. If you guys like this episode, you are going to love this tool called interview simulator. I recently released it, interviewsimulator.io. That's interview simulator.io. It's called interview simulator because it simulates an interview where you basically will have this exact same scenario with me, where I ask you a question, you respond with video or audio. You get to see how I would answer the question and then we also have an AI interview wizard that will give you critique. It'll score your answer on 1 to 10 and also give you a list of pros, things that you did well and some areas where you could maybe improve. So, if you guys want to check that out, interview simulator.io. Let's get into this episode. you prepared for an interview question? Yeah, I'm in a graduate school and I'm just looking for kind of like internship and the full-time job within a data analytics side, so I think this is a good chance to practice. Well, first off, congrats on grad school and for being here and being brave to do this. The questions that we're going to be pulling from today are going to be straight from interview simulator. So, you can answer them today and then you can always go back and practice them here. We'll start off with a behavioral question and then we'll move to a technical question. Let's go ahead and hop into it, Richard. Okay, so we're going to start off pretty simple and because I don't know anything about you. We're going to start off with the question that's probably going to be asked in every interview, and that is tell me about yourself. So, Richard, tell me about yourself. Yeah, sure. Yeah, my name is Richard, and I'm a graduate school from the MSBA program. I'm on the second semester, and I'm very interested into the utilizing the data and AI in my field. For my work experience, I would work for the data analysis, data engineer, and BI engineer for three years. And for during that times, I will utilize over 10 products and built for the data pipeline for the various companies, including Adpec, PropTech, and Financial FinTech area. That was a great answer, and it's it's always scary giving those answers. Always, especially on on a live call like this, so that that was a great answer. I like that you kind of identified what you're currently doing, right? You said you're a graduate student. That's always key to make sure that like they know what you're actually doing right now. But I also like that you said what you've done in the past. So, yeah, you said you'd been working like as a data analyst for three years. I I and it seemed like you you had done it in a couple different industries. I didn't catch any of the company name. So what companies did you work for? Yeah, I worked for the BYU Pathway and the other is, sorry, I forgot the names of the the prop companies. It was located in Arizona. Okay, cool. One of the other things I thought it it sounded like at those companies that you'd worked for. You have like you developed some experience and you said you'd use multiple tools. What were some of those tools? I would like to know in that answer like what tools. So what tools did you did you use? Yeah, for the dashboard building, I've used the Tableau, Power BI and the QuickSite, and for the data pipeline, I most likely use the AWS stack, which is the glue and the Athena for the data wrangling and cleansing. Oh, see, that's super awesome and very impressive. Yeah, so that I think that would be my my critique is mentioning the companies and the tools by name. Because like AWS is no joke. It is not the easiest tool stack to use. That's like, oh, I'm already thinking, Richard knows knows some pretty good stuff. So that's great. I think that was really important to add those things to your answer. But I thought I thought you did a a fairly good job. One of the cool things is you can go back and go to interview simulator.io and practice the question here. You know, with either video or with audio, and it does a pretty good job. You'll get a response from our interview wizard that basically looks at your answer. Analyzes it, gives it a score, one out of 10, and lists the pros and the cons as well. And then also let you watch the the replay as well, because even when you were answering the question, me as a human, I was like trying to remember every single thing that you said. That's the nice thing about the interview is, is it's not human, so it doesn't have to try to remember. So anyways, I think your answer, I I'd probably give your answer probably around a seven or an eight out of 10, I think. I think you did a good job identifying of what you've done. You made me feel confident that you I was like, oh, Richard does have, you know, experience in the past. And I think to to make it like a nine or a 10 out of 10, adding a little bit more specificity around the the text stack and the tools would probably be the key there. Does that make sense, Richard? Yeah, totally makes sense. Thank you. Okay, cool. You down to do a technical question? Yeah, I'm ready to do that. I think. Okay, let's try a technical question. I'll actually let you choose out of these questions you see over here on the screen. Which technical question? Because technical questions are a little bit scary in my opinion. So I'll let you choose since you've been brave. Which technical question would you like to answer today? Yeah, I think the SQL window function from Amazon would be interesting for me. Okay, let's go ahead and do it. So, I'll pull this up. Once again, I'm not going to play the video of me asking the question, like you normally would in interview simulator, because I'm here live with you, right, obviously, so it's probably not necessary. But basically, in this question, which is taken from an Amazon, I think this is actually taken from a business intelligence engineer position at Amazon. And let's go ahead and I'll ask you the question. The question is, what is a SQL window function and when would you use one? So, I'll open it up to you, Richard. Go ahead. Yeah, for the window function, I think it is very similar for the group by or aggregated function, but you can do without just aggregating for that one. Uh or or transforming the original or low dataset. So, for example, like if you want to partitions by one of the data for each of the users, for example, then you can just like doing group by and just like aggregating some of the the numbers or counting the numbers for example. But uh window functions allow you to just like without group by, you are just like maintaining some of the the original dataset and you are just like adding some of the aggregated numbers on to the dataset. So like, for example, count up the how many users are existing per each of the men's or women, then if you get in seven in total, then you will get the number of each each low as a total of seven by using the window function. Sweet! Clap it up for for Richard, you guys. That was a great answer and he did a good job. That is not an easy question. The SQL window function at all. Richard, I think you did a great job on this question. I think I loved the thing I really once again, so just just to kind of highlight, you can always go back to interview simulator and ask, you know, go through the exact same question again. And you would actually be able to watch your answer back. You would actually get to see me answer the question and then, of course, you'd get your feedback from the interview is in interview simulator as well. If I had to guess what interview is would say about that question, I honestly think that was probably an eight or a nine out of 10. You pretty much nailed everything. So things I'm looking for when when I ask this question is, yeah, saying it's like a group by without aggregations, I think is probably the easiest way to describe it, like in simple terms. I think that's really good. And then you said for example, twice, which I think is always good trying to give like a tangible example of when it's useful. So I think that's really good. And it it's like way easier to show like a table of it being used versus explaining it via word, so I think you did a good job with that. My only critique would probably be to talk I mean, you did kind of talk about it with that girls and boys example. I guess I was kind of looking for like some some common use cases, like some of the and you kind of gave it. I think you were what you were talking about the boys and girls was like a running count. I was looking just for that word, like a running sum or like a running count or like a running a rolling average or something like that. So I think that that would have been the only thing that could have made it a little bit better, but overall, I think that was a pretty good answer to a pretty tough SQL question. What do you think? Does that make sense? Yeah, I think it'll be better to if I just give the link example so that like people can easily understand it like how the window function can be applied to just make the length of each of the laws. Yeah, 100%. But overall, I feel like that was pretty solid and I think you did a a great job. Everyone clap it up for Richard. That is not easy to do and come up here on this stage. Speaking of which, we have someone new to the stage. Joey, welcome to our show today. Thank you so much for having me. Hey, no problem. Thanks for being brave. I know this is a hard thing to to do. Where are you calling from today? Calling in from Houston, Texas. So I've been following you. You know, Lin and you're one of the main reasons why I achieved a lot of my success. I recently I accepted a an offer with Comcast MBC Universal as a senior business of thousands analyst. But I always constantly on the lookout to improve my interview strategies. I have an interview coming up tomorrow, well, a presentation on how to deliver the best interview tips. So I was looking forward to learn about yourself and, you know, all this new platform that you have. Sweet, that is awesome. And congrats on the new job. I'm going to challenge you, if you don't mind. Let's do one of these like logic thinking questions. This one is from Airbnb. All of you guys watching, you guys can try it at interview simulator.io. But the question is, how many meeting rooms? So Airbnb, once again, I'm not going to press play on the question. That's how you do it in real life, in interview simulator. But basically, Airbnb is looking to expand and they're building a new headquarters. And they're trying to think through, how many meeting rooms should they put in this new headquarters? They're asking you as, you know, a data analyst to try to solve this problem. So, Joey, go ahead. How many meeting rooms should we build as Airbnb? Sure, absolutely. First, I would have to start off with how many people are we intending to to relocate to this office for example. I would also want data on sort of the the department titles, you know, I would imagine meeting moves would be mostly taken up by folks in the upper, you know, level executive rights.
[11:07]I also would ask data on, you know, the number of hours, you know, are there like peak times that, you know, certain, you know, executives or teams meet more regularly? I would imagine that, you know, traffic, you know, a lot of meetings take place in the morning with those sporadic ones coming up in the afternoon. But if you can guide me more through this, I'll really appreciate it. Okay, great. So, yeah, let's say we're going to we anticipate around 3,000 people being at this building. There is a little bit of a hybrid schedule, however, so, you know, it might not be 3,000 every single day. Let's say 20,000 square feet. So, 20,000 square feet, absolutely. So, now that we have sort of, you know, I think also information on the meeting culture. So, sometimes employees, you know, take on virtual meetings, right? Let's assume that 25% of those employees are in meetings at any given time. And so, we would say the average meeting size can be anywhere from, I would say, 5 to 10 people. Of course, there can be more people in the meetings, there can be less. And so, with that being said, I would say each room can be used around, you know, 60 to 70% of the time, with 30% is where like, you know, just being used like by people that just come into the meeting rooms to just get work. So, I would say based on the assumptions, so, the total number of people in these meetings simultaneously can be 20,000. So, right area of the ones that you just mentioned, I would multiply that by 25% of the employees that are in meetings every time. So, 20,000 times 25%, I would be around, you know, I would say, let me let me do the math. 2,000 by 25%, 5,000 people, right? And so, the number of meeting rooms that are needed based on the average size, I'd say the average meeting size is 4 to 6 people. So, I would go around with 5 people, I would divide that by 5, and so that would be, that's not that that doesn't make sense. So, 1,000. I think I think I I I confused you because I I think I said, I accidentally said 20,000 employees, but I really meant 20,000 feet, or square feet. But regardless, I think this was a pretty good answer. I think you did really well because like basically, these questions, they're just trying to see how the heck do you think, like, what is your thought process? And you did a really good job of basically you're almost like streaming your full of of consciousness and like thinking through everything. I love that you like pulled out a calculator. I thought that was that was really good. And you're and I love that at the beginning how you like asked for clarity. I think that's really important and something that's that that a lot of people probably don't feel comfortable doing in an interview all the time is like, can you can you explain a little bit more? So, I think I think you did a really good job. I love what Daniella just said. Daniella says, OMG, these questions made me realize I need to do more mock interviews. Well, that's that's good. And that's the point of interview simulator is to get questions like this and to take a stab at at answering them. Because like, I mean, Joey, correct me if I'm wrong, but I'm assuming that you don't like spend your time every day, even as a as a data analyst, even as a senior data analyst, like really thinking through how many meeting rooms a a building should have, right? Absolutely not, but I think where the value comes in is your thought process and your ability to think critically, and I think that is what, you know, when we're talking about the AI era, the the ability to think critically will take us far and make sure that we will not be replaced, right? Because that's sort of the trend that we a lot of people say we want to be replaced by AI, but I think that ability to think critically is what will make us stay. Yeah, 100%. And so these types of questions, I mean, of course, every day you're thinking critically. But it's like, you're not thinking critically out loud on like this type of a weird question. So, really practicing, like Daniella said, like doing these mock interviews is really useful. But but I thought you did a good job. And like in the end, I don't even know, I might have cut you off before you actually gave a a real number. But that's not the point of the interview is or the question is like, we don't actually care about what number you actually end up saying. It's more what did you lead up before the number? I thought you did a good job asking for clarity, asking for more data. You know, going through it almost looked like or or it almost felt like you had like a Google sheet or like Excel open and you're like putting these numbers in and and kind of crunching it. And I I as the interviewer could be like, okay, yeah, I can see how Joey could solve these types of hard problems at our company. So, I thought you did a good job. I think on a rating, I would give you probably about an eight or a nine. The only thing I think that you could improve on is probably just not having to do it in front of people on LinkedIn and have like like a piece of paper in front of you just to keep track of it all. That's being me being nippy. I thought you did a a great job. So, it'd be fun for you to test this out on interview simulator.io. And and see what interview is things your answer because I thought it was pretty good. Yeah, absolutely. Thank you so much, Avery. So, I'll be presenting this. Uh, I have to take a screenshot of this. And uh presenting it to my presentation uh tomorrow with Blac Tech and Technology. So, uh, you know, promoting, helping you promote this. Hey, I I appreciate it, Joey. Thanks so much for being brave and coming up and uh let me know if there's anything I can do for that as well. Absolutely. Thank you so much, Avery. Have a good one. I recently released a mock interview tool. It's called interview simulator. You guys can check it out at interview simulator.io. Um, for the next 14 days, it is completely free. Um, and you guys can just click this button right here, try interview simulator and just enter your email. Boom. And you will be taken to this page right here, which is where we have all of our questions from all our different companies. And you can try a question from Apple, a question from Airbnb, or a question from Chevron, from the NFL, from Netflix. That good stuff and practice using audio and video. You basically will click on a question. You'll hear me ask the question, and then you'll be able to respond via audio or via video. Once you give your response, you'll actually hear me respond, give my like example response. And then we are going to give you a grade from the interviewwiz. The interviewwiz is our AI tool that will look at your answer, give you a score from 1 to 10 and list all the pros and the cons like what you did well and where you could improve. And we'll also be adding expert examples down here at the bottom as well from other students inside the program as we expand. You guys can find the link in the comments. Thank you guys for joining. I'm excited to be doing this more in the future and we'll talk soon. Have a good day, everyone. Bye bye.
