Alex The Analyst Q/A Livestream | Come Ask Me Anything - video Dailymotion

Alex The Analyst

Come ask me anything in my Weekly Q/A!  In this weekly series you can come and ask me questions about all things Data, Analytics, Tech, or anything else you could want.  Get 2 Weeks Free! https://analystbuilder.com?promo=2WeeksFree  Already a Member? Get 35% off any purchase with code: 35OFF ____________________________________________   SUBSCRIBE! Do you want to become a Data Analyst? That&#039;s what this channel is all about! My goal is to help you learn everything you need in order to start your career or even switch your career into Data Analytics. Be sure to subscribe to not miss out on any content! ____________________________________________   RESOURCES:  Coursera Courses: 📖Google Data Analyst Certification: https://coursera.pxf.io/5bBd62 📖Data Analysis with Python - https://coursera.pxf.io/BXY3Wy 📖IBM Data Analysis Specialization - https://coursera.pxf.io/AoYOdR 📖Tableau Data Visualization - https://coursera.pxf.io/MXYqaN  Udemy Courses: 📖Python for Data Analysis and Visualization- https://bit.ly/3hhX4LX 📖Statistics for Data Science - https://bit.ly/37jqDbq 📖SQL for Data Analysts (SSMS) - https://bit.ly/3fkqEij 📖Tableau A-Z - http://bit.ly/385lYvN  *Please note I may ea

Transcript

00:00:00All right. Hello, hello, hello, everybody.

00:00:04Give me just a second.

00:00:05I'm just going to make sure everything is working good on my site.

00:00:08Then we'll get started.

00:00:09Thank you guys for people who are already here.

00:00:13So once I see it on my screen, we're good to go.

00:00:16I'll start, you know, the whole process.

00:00:19But this is my weekly live stream.

00:00:22This is what, here it comes.

00:00:26There we go. It's working great.

00:00:28This is my weekly live stream.

00:00:29I've been doing this for almost two months now.

00:00:32And so I just do it every Thursday at 9 a.m.

00:00:36to answer your guys' questions.

00:00:38And it's been really, really fun.

00:00:40I got to talk to a lot of people, answer a ton of great questions.

00:00:44So in previous live streams, I've answered so many different questions.

00:00:48It's a pretty wild, the array of questions.

00:00:51Hey, everybody.

00:00:52I see everybody in the chat.

00:00:54Nick, Rossi, Sandeep, River, Cassandra, lots of – there's a few people I recognize, some new people, and lots of

00:01:05people I recognize.

00:01:08Feel free to let me know where you're at right now.

00:01:10I'm always just interested because I get people from all around the world listening to this live stream.

00:01:16It's really fun.

00:01:17So, oh, from Pakistan.

00:01:18Pakistan, very nice, very nice.

00:01:22So how this usually goes is I'm just going to answer questions for, like, 45, 50 minutes.

00:01:28And at the very end, usually lasts about 5 to 10 minutes, I do a giveaway.

00:01:33The giveaway is of my courses.

00:01:35I've created my own courses on SQL and Python and a bunch of other stuff on analystbuilder.com.

00:01:41And I'm just going to give them away for free.

00:01:43So all you have to do is have an account for that, and I'm going to give away for free.

00:01:46Okay, we got Braby from North Carolina.

00:01:50I used to live in North Carolina.

00:01:50We got Ivan from the Czech Republic.

00:01:53Let's see.

00:01:54Saudi Arabia, Brazil, Indy.

00:01:57I'm not sure if that's India or Indiana, but welcome, Pakistan.

00:02:01Pakistan, Kenya, awesome.

00:02:04India, hey, everybody.

00:02:06This is awesome.

00:02:07I love seeing so many people.

00:02:09I know it's the morning my time, so it's 9 o'clock in the morning.

00:02:13I just, my kids just went off to school.

00:02:16But, you know, I know in other places it's, like, nighttime, middle of the night.

00:02:22And so thank you guys for showing up.

00:02:24Malaysia, Kenya, Canada, Massachusetts, Nepal, Nigeria, Ethiopia.

00:02:29I'm just reading them live.

00:02:31There is a slight delay.

00:02:32I don't know if you've noticed, but there's a slight delay.

00:02:34Now, listen, I'm one guy.

00:02:36I don't know if my moderators are in here yet, but I'm only one guy, and there's a delay.

00:02:41So if I don't answer your question right away, don't spam it, or I'll block you.

00:02:45It just is a thing.

00:02:46It's not fun.

00:02:48Zimbabwe, Ethiopia, Indonesia, Nepal, awesome.

00:02:52I am so happy to have you guys here.

00:02:55This makes me really happy just to have so many people.

00:02:58Some names I recognize, some I don't, which means there's new people.

00:03:02So thank you guys for joining.

00:03:03You guys can go ahead and start asking questions in the chat below.

00:03:08Or in the chat, not below.

00:03:10To me, it's off to the side.

00:03:11But go ahead and start asking questions.

00:03:13I'm just going to dive in.

00:03:14We're just going to start answering questions.

00:03:16It can be about anything.

00:03:18Well, I mean, I may not answer every single question, but if it's on topic, if it makes

00:03:23sense to answer, I will try to answer it.

00:03:26If I don't have a good answer, I'll hopefully give you somewhere to look to go ask somebody

00:03:31else or, you know, who knows what the answer will be.

00:03:36All right.

00:03:37This question comes in.

00:03:38Let's see.

00:03:40Hi, Alex.

00:03:41What will be the future of data analytics?

00:03:44Do we need to learn generative AI too?

00:03:48I mean, I think everybody should be picking up AI in some way.

00:03:53I don't have all the answers to this, and I've talked so much about it in previous live streams.

00:04:00But here's what I'll say is AI is going to change things, right?

00:04:03It's going to help generate reports or dashboards or processes or different things.

00:04:09But I do believe that people are going to be really important in this, especially since

00:04:14as of right now and at least for the foreseeable future, the AI is not perfect.

00:04:18And as long as there's mistakes being made, we need systems in place, people in place,

00:04:23and people who have the domain experience and the ability to work with people.

00:04:28We need those things.

00:04:29They're still extremely important.

00:04:31They have not in any way been replaced, at least for data analysts or really the data

00:04:37people in general.

00:04:39But learning AI is really important.

00:04:41Something that is just like really neat that I've been kind of looking into and learning

00:04:46about is synthetic data, which has been really interesting.

00:04:49It's where you can create data based off of different ideas and hypotheses, and you can

00:04:56test different types of analysis against this synthetic data.

00:05:01I think it's super cool.

00:05:02It's a really cool use case, but as of right now, as of what I see the foreseeable future

00:05:08for the next five, 10 years, I don't see data analysis or data analysts going away.

00:05:14All right, let's keep looking.

00:05:15Is it possible to get a data analyst remote job, especially in a country where tech isn't

00:05:19a big thing?

00:05:20It is.

00:05:21It definitely is possible.

00:05:23It was much more possible in like 2020, 2021, 2022, when everybody was hiring and remote

00:05:30jobs were everywhere because of COVID, but remote jobs are a lot less now.

00:05:35A lot of companies have gone back to in-person work, and so remote jobs are much more competitive

00:05:41because you have so many people around the world trying to get them at the same time.

00:05:44That's really tough.

00:05:46So my best advice is if you're trying to get a remote job to start making connections, talk

00:05:55to previous employers.

00:05:56If you went to school, go back to your school and try to get some connections through your

00:06:02school, or sometimes they have career programs or career departments that help people get

00:06:10jobs.

00:06:11That is what I would say.

00:06:12Some people have also had success doing freelancing on things like Upwork and Fiverr, but I don't

00:06:17have experience in that, so I won't talk about it too much.

00:06:22Let's see.

00:06:25What kind of tools should we learn as a sustainability analyst?

00:06:30I don't know much about, I haven't heard sustainability analysts much, but in general, great tools to

00:06:38learn are SQL, Excel, and a BI tool.

00:06:40Those are like the staples, the basics.

00:06:42What I do recommend, and I've been recommending more and more and more, is learning the cloud,

00:06:47learning AWS and Azure.

00:06:48You can learn Google Cloud Platform, but I personally don't like Google Cloud Platform.

00:06:53I've used it many times, and I liked Azure and AWS way more, and more companies use it.

00:06:59So that's up to you, but you can learn those.

00:07:01But I highly recommend learning those because so many companies use them, but not enough people

00:07:06know how to use them.

00:07:07And so there is kind of a bottleneck for talent and skill in that area.

00:07:11Yeah.

00:07:13Elijah Butler, I have a question.

00:07:15How dare you?

00:07:16Oh, hey, Elijah.

00:07:17Thanks for joining.

00:07:18I appreciate it.

00:07:19I don't have an answer to your question.

00:07:21I'm just doing my best, man.

00:07:24Just give me a break.

00:07:27All right.

00:07:28This is Rapperskipif.

00:07:33Is it necessary to learn Pandas deeply as a data analyst?

00:07:36No, it's not.

00:07:38I would say the majority of companies won't use it at all, right?

00:07:41I would say, you know, there's going to be 5% to 10% of companies that use it in

00:07:47some way.

00:07:50Deeply use Pandas or the advanced stuff within Pandas.

00:07:54It's going to be even less.

00:07:56But that doesn't mean that you can't use it, right?

00:07:58When I first started in one of my previous roles, they didn't use Python at all.

00:08:02But then I started, I was learning Python.

00:08:03I was like, hey, I could maybe automate some things or do create some scripts and do some

00:08:08stuff that I, or kind of automate some of the things that I don't really want to do.

00:08:13And I asked my boss and they were like, yeah, absolutely.

00:08:15Go for it.

00:08:15And I did it.

00:08:16And then people, other people implemented it and liked it.

00:08:19So it doesn't have to be something that, you know, maybe your company uses.

00:08:22But if you know how to use it, that can be a very good thing.

00:08:27Tushar223, which AI tool should one use for data analytics?

00:08:31Honestly, they're, they all, I'm not going to say they're all the same because they're not.

00:08:37But if you're doing a lot of coding, Cursor is a really good one.

00:08:41I've been using Cursor.

00:08:42I like GitHub Copilot.

00:08:45ChatGPT is just a really good one to use by default for a lot of different things.

00:08:50But, you know, you can use Copilot.

00:08:51You can use Anthropic.

00:08:53There's lots of different variations and ones out there.

00:08:55In terms of tools, you'll notice as time goes on that there's just going to be a tool,

00:09:00an AI tool for everything.

00:09:02There's going to be an AI tool in Tableau.

00:09:04There's going to be an AI tool in, you know, GitHub.

00:09:07There's going to be an AI tool in AWS.

00:09:09There's going to be an AI tool in Azure.

00:09:10And just learning how to use AI, how to create prompts, how to work with them, how to get them

00:09:17to actually do what you want,

00:09:18because that can be very tricky.

00:09:20That is a real skill set.

00:09:21So just learning how to use AI in general.

00:09:23There isn't one tool for data analytics, though.

00:09:25There's never going to be.

00:09:27Let's see.

00:09:30That's a good one.

00:09:31So Natasha the Gray, the Gray Jedi.

00:09:34Cool name.

00:09:35I don't know what that means, but it's a cool name.

00:09:38Good morning, Alex.

00:09:39I'm already learning data analytics myself, but I'm curious how much statistics you usually use on a daily basis.

00:09:45So I'll give you my experience, and then I'll give you other people's experience,

00:09:49and then just some information on it.

00:09:51So statistics is important, right?

00:09:53Math does play a part.

00:09:54You can do basic statistics where it's, you know, mean, median, standard deviation, averages, things like that.

00:10:02Really, I would say, like, the core statistical concepts, if you want to call it even statistics, just basic math.

00:10:11But then you can get more advanced.

00:10:13You can get into certain types of distributions or regression analysis or some forecasting has a lot of statistics in

00:10:22it.

00:10:24But how much did I actually use?

00:10:26I would say I mostly stuck with the basics.

00:10:28We did a little bit of, like, linear regression, especially when I was working on, like, a data science team.

00:10:34But that was within healthcare, a lot of healthcare.

00:10:36We didn't use a ton of statistics.

00:10:39That was mostly the data scientists on our team did a little bit more statistics than I did.

00:10:44And we had a statistician who did pure statistics.

00:10:46That's all they did in their job.

00:10:49But I have heard that a lot of finance, banking, finance jobs, when it comes to analysts, they typically use

00:10:56a lot more statistics than other domains.

00:11:00And so take that with a grain of salt.

00:11:01But that is kind of just some general knowledge.

00:11:05How did you break away?

00:11:06This is a 10 days in.

00:11:08How did you break away from the 9 to 5?

00:11:10It was purely through luck and just, I don't know.

00:11:14I think ignorance played a nice part in it.

00:11:17A little bit of ignorance goes a long way.

00:11:19I didn't realize how difficult and how much time I was going to be putting into YouTube and all these

00:11:25other things in my life.

00:11:26But back in 2020, I started a YouTube channel, the one you're watching now, called Alex the Analyst.

00:11:31And I just kept posting.

00:11:33I really had a passion for it at the time.

00:11:36I still have a passion for it today.

00:11:38But I kind of lucked into people, started watching it.

00:11:42And that grew my channel.

00:11:43And then my LinkedIn started growing.

00:11:45And so I started, you know, having people reach out to me and having people ask, hey, do you do

00:11:52any consulting work?

00:11:53That video that you made is the exact same thing we're trying to do at my work, but I can't

00:11:57figure it out.

00:11:58Would you help us out?

00:11:59So I started doing some consulting on the side and then got promotions at work.

00:12:03And then eventually my side consulting was making about as much as my full-time job.

00:12:08And so I was like, all right, let's dive into the consulting stuff.

00:12:11Let me really, you know, do that.

00:12:14And so I quit my job, started doing consulting, Alex Analytics LLC.

00:12:18It's on my LinkedIn.

00:12:19Started doing that full-time.

00:12:21And then, you know, just kept doing my YouTube stuff on the side.

00:12:24And then built Analyst Builder, which is my ed tech platform.

00:12:28And so, you know, now I do consulting and I have people on Retainer and I do my full courses

00:12:34and, you know, interview prep on Analyst Builder.

00:12:37And that's how I did it.

00:12:38I kind of just started my own thing.

00:12:40But it was mostly by luck, I would say, is like 50% of it.

00:12:44But posting, if I didn't post, if I didn't create videos, if I didn't post on LinkedIn or Twitter or

00:12:49all these other places, I would have never gotten that lucky.

00:12:52So, you know, it's like half skill, half, you know, putting in the effort and putting in the work.

00:13:01Hannah Mariam Chanyalu, is data analysis a dead job?

00:13:05No, it's not.

00:13:07You know, there are always going to be pieces within data analytics that can be automated.

00:13:13And that's been the case for a long time.

00:13:16I don't think AI is going to come in and automate a ton of data analysis.

00:13:23I think it will help with, you know, things like data quality checks.

00:13:29But it doesn't do well with handling large data sets at the moment.

00:13:32It hallucinates a lot with anything over, like, a few thousand rows.

00:13:35So, that has a lot of improvement there.

00:13:37But it is going to be helpful with generating dashboards.

00:13:40I think that's the place where it's most helpful right now.

00:13:44Data analysts in general don't do an immense amount of coding.

00:13:48So, you know, you're not going to see a ton of things like AI agents coming in and doing a

00:13:54ton of data analysis work.

00:13:55Because a lot of what we do is very hands-on, methodical work, working with the clients, understanding what they

00:14:03need, going back, cleaning the data, creating automations around that.

00:14:09And a lot of that is not going to be AI.

00:14:10That's going to be things in SQL, things in AWS and Azure.

00:14:14And AI will help with these things.

00:14:16But as of right now in the foreseeable future, I don't see them as, you know, big replacers for us.

00:14:24Really, the loss of jobs in the whole tech world right now is mostly due to the economy.

00:14:30Not a ton of them is due to AI, although some of them are due to AI.

00:14:35Diksha Bardwaj.

00:14:37Hi, Alex.

00:14:37What is the best sites to practice SQL for a beginner?

00:14:40All right.

00:14:40This is a plug for myself, and I truly believe it.

00:14:44I built a whole platform called Analyst Builder.

00:14:46It is the best place to practice SQL.

00:14:51100%.

00:14:51I fully believe that.

00:14:53There are other places.

00:14:54And you can get two weeks for free in the description below, by the way.

00:14:57Just two weeks.

00:14:58Just to try it out.

00:14:59Just go take a full course.

00:15:01Try out our questions and our general questions.

00:15:04It's great.

00:15:05Other places, you can go to LeakCode.

00:15:07You can go to Stratuscratch.

00:15:08There's DataLemur.

00:15:09There are other websites that do what I would call practice questions, but those platforms

00:15:15don't have courses built in where you can practice in the courses as well.

00:15:20So that's what makes our platform unique.

00:15:22We kind of put it all in one.

00:15:24Instead of paying three different subscriptions or buying on four different platforms, we put

00:15:28it all into one.

00:15:29It's pretty great.

00:15:32Let's see.

00:15:34Your audio is low.

00:15:36I know.

00:15:36It is.

00:15:38Maybe if I just like, all right.

00:15:40Is this better?

00:15:42Can you guys hear me better now?

00:15:44I bet you can.

00:15:45I bet this is actually better.

00:15:47But I'm not going to keep it like this because this doesn't look great.

00:15:53But I'll keep it like this for just a second.

00:15:55Maybe the audio is like really good now.

00:15:58Barat Matters.

00:15:59How to get an internship for data analysts before getting a job.

00:16:02Honestly, I never did an internship.

00:16:04The only experience or information that I have on getting an internship is from what

00:16:10I hear from other people.

00:16:11There are websites that are specifically geared towards internships.

00:16:17One second.

00:16:18Matthew Alderman.

00:16:19He's in the house.

00:16:20And he's my moderator.

00:16:22He's one of my moderators.

00:16:23Thank you, Matthew.

00:16:25Tell him how it is.

00:16:26Block him.

00:16:27Tell him to don't spam.

00:16:29Anyways, I'll answer your question.

00:16:31But I don't personally have any experience in that.

00:16:33What I've heard is just there are websites specifically geared towards internships.

00:16:37There's also internships you can get through like LinkedIn and stuff.

00:16:39But also, especially if you've gone, you know, you got a degree from college, they want

00:16:42you to get internships.

00:16:44And so they'll partner with previous alumni.

00:16:46And so I would recommend reaching out.

00:16:49Excuse me.

00:16:49I'm burping already.

00:16:51This is just starting early.

00:16:53I would recommend, you know, looking at your college and seeing if there are any opportunities.

00:16:57A lot of personal connections, do internships.

00:17:00That's where most people will get them.

00:17:01It's just from people they know.

00:17:03Moms, dads, cousins, uncles.

00:17:06It is true.

00:17:08That's what I've heard.

00:17:11Let's see.

00:17:14RRM.

00:17:15Hello, Alex.

00:17:16Suggest some project topic for healthcare domain.

00:17:18Well, you're asking the right person.

00:17:20Healthcare is like my specialty.

00:17:21I could list off 100 projects.

00:17:24I love healthcare.

00:17:25Some of the best projects that I would say that are things that are helpful for landing

00:17:30a job.

00:17:31So this would be, you know, things that are incorporated in a lot of areas of healthcare

00:17:37would be looking at claims data.

00:17:39So either analyzing some claims data, creating some sample claims data, creating some dashboards

00:17:43around claims data.

00:17:44That stuff's really important.

00:17:45What's really impressive is using things like, you know, coding, not coding software, coding

00:17:54systems within healthcare.

00:17:56So that's called like LOIC codes, ICD codes, CBT codes, HCPCS codes.

00:18:00All of these codes are used all throughout.

00:18:03And so I would start with like ICD and CBT codes because those are used the most, especially

00:18:07with front care providers when they see people.

00:18:11I would use those and create some, you know, look at that and then have like a data set where

00:18:16you have patients and their diagnoses.

00:18:19And then there's another table with ICD codes and you can pair those together and you can,

00:18:24you know, create reports out of that.

00:18:26That's a good idea.

00:18:27I could go on and on, but those are like the two big ones I would look at.

00:18:31I think those are pretty interesting.

00:18:33All right.

00:18:33Let's see.

00:18:36Let's see.

00:18:42I'm just reading through questions.

00:18:43Some of these I've already answered.

00:18:45All right.

00:18:46This is a good one.

00:18:47Godwin Emmanuel.

00:18:48It says, how do you think I can get the best results from self-learning?

00:18:52I struggle with being consistent.

00:18:54I think that's like the majority of people out there.

00:18:58I think that consistency happens when you have a good direction, like you have a good path

00:19:05to follow.

00:19:07Um, uh, it is difficult and there's so many different situations.

00:19:12I'll just give you two separate examples.

00:19:14One, someone's working a part-time job in the day and they have the rest of the day to

00:19:18themselves because they don't have like a family or anything.

00:19:21They just work a part-time job.

00:19:22They come home.

00:19:23They're gonna have a lot of free time and it's going to be easier to be more consistent.

00:19:26Then this other person is, you know, they have a full-time job.

00:19:29They're supporting a family.

00:19:30They come home.

00:19:31They're putting kids to bed.

00:19:32They're doing all this stuff.

00:19:33It's gonna be much more difficult.

00:19:35So, you know, take everything I say with a grain of salt.

00:19:37What I would say is, is have a path.

00:19:39That's why I created the data analyst, uh, uh, bootcamp.

00:19:42It's free on my YouTube channel.

00:19:44It's like 24 hours of content.

00:19:45I'm about to make it like 28 hours.

00:19:47I'm going to release a new one with my R series and my getting GitHub series, which I start

00:19:51next Tuesday.

00:19:52But I'm going to release like at the end of next month, um, I'll release like a 28 hour,

00:19:5629 hour bootcamp for free.

00:19:58That is something I would follow because it takes you through the exact steps of things

00:20:01you need to learn.

00:20:03And it's a one video.

00:20:05So you can just keep following along and stay consistent on that one video.

00:20:08That is a great path to follow.

00:20:10So, um, you know, I also think blocking time out, taking away distractions, uh, I know when

00:20:17I was first learning, I stopped watching Netflix and stopped watching YouTube and stopped gaming

00:20:22on my phone.

00:20:23I, instead, I was only studying mostly SQL.

00:20:26Um, Matthew, thank you for the $5.

00:20:31That's for my, uh, at this point, this was like, um, this is like a monthly, a weekly

00:20:37subscription at this point, you gave me $5, uh, I will use that.

00:20:41I haven't had my Wendy's, uh, although it's inflation, you know, $6 biggie bag now, but,

00:20:46um, I haven't had Wendy's in a while and I need it.

00:20:49It says CTEs are always the solution.

00:20:52Um, look, Matthew, I don't want to rain on your prey.

00:20:56It's not always the solution.

00:20:57I mean, sometimes it's other things, but yeah, CTEs and SQL are great.

00:21:01I love CTEs.

00:21:02I use them all the time.

00:21:05Um, all right, let me see.

00:21:07Let me see.

00:21:09If you have a LinkedIn handle, drop it, drop it mine.

00:21:13I don't know.

00:21:14Wisdom.

00:21:14I don't know what that means.

00:21:15Uh, but yes, I'm on LinkedIn.

00:21:16Go ahead and find me on LinkedIn.

00:21:17Just search Alex Freeberg or Alex, the analyst.

00:21:20You'll find me.

00:21:21You'll find me.

00:21:22Um, I'm a, I'm a, uh, this is John Ode Hiambo.

00:21:28Alex, I'm perusing pure.

00:21:31I'm guessing pursuing, uh, pure mathematics and applied statistics.

00:21:35Is it good to practice data analysis?

00:21:37Absolutely.

00:21:37Uh, you will find when you start working in mathematics and statistics, you'll eventually

00:21:43go down a rabbit hole towards some type of data heavy side of things, right?

00:21:48Collecting data, using data, understanding how to use data.

00:21:53Um, for statistics, a lot of people in statistics will use R or Python, uh, for their coding.

00:22:00There's also other coding languages that they might use, but you know, R is a popular one

00:22:04for statistics.

00:22:06Um, but knowing how to think like an analyst and use and manipulate and work with data is

00:22:12something mathematics, uh, and statistics will do a lot.

00:22:15Um, all right, let me see.

00:22:27Gamer gin I X.

00:22:28Can you create a video about data cleaning in Excel?

00:22:31And is it possible to no values to replace them with mean like Python fill in a, I have

00:22:36a whole video.

00:22:37I have a whole Excel series and I do a whole video on data cleaning.

00:22:42So go ahead and I already have that.

00:22:43So I'm not going to make it.

00:22:45I already have it for you.

00:22:47I hope that's helpful.

00:22:49I've been Habas to have Habsadu.

00:22:52Hi, Alex.

00:22:53I want to start my journey with P as a people analyst.

00:22:56That's a cool title.

00:22:57Uh, I've heard, I've heard that's like a new job kind of thing that's coming out.

00:23:02It's like, uh, the people operating officer.

00:23:07That's not a good acronym, but it's like a people focused role, um, at a lot of companies,

00:23:13which is really interesting.

00:23:14It says, do the, do you lifetime access to analyst builder would help me start?

00:23:19It absolutely would, but it does cost money, right?

00:23:23I, I'm not here to force you to buy anything or even really push it that much.

00:23:29I really think that my free data analyst bootcamp on YouTube is the place to start.

00:23:34Like if you're just starting out and you're not a hundred percent sure, start out with

00:23:38my free data analyst bootcamp and follow that all the way through.

00:23:41If you like what you see, you're like, man, I'm really learning a lot and I want to go

00:23:44even more in depth and I want more advanced projects and, and you know, you want more

00:23:48then that's when you would go to like analyst builder.

00:23:51Um, unless you just want to deep dive in right away, which some people do.

00:23:56Um, but, but my free data analyst bootcamp on YouTube is really great place to start.

00:24:01Uh, soul edits.

00:24:03I listen, I don't want to make this all about, if you have a, if you have questions about

00:24:07analyst builder, email support at analyst builder.com.

00:24:11Um, what kind of projects should we put in or should we build for a portfolio?

00:24:17I think there are some, I think what you should start with, I can, I'm keeping this here.

00:24:22Is this fine?

00:24:22Is this okay?

00:24:24I don't know if I should keep this here or not.

00:24:26Now I'm just kind of doing it.

00:24:26I forgot about it.

00:24:27I forgot it was here.

00:24:29Whoops.

00:24:30Um, all right.

00:24:31I think everyone should start with guided projects.

00:24:34Guided projects are the best way to learn when you're starting out.

00:24:38And that's why I do so many guided projects on my YouTube channel.

00:24:41All of my projects at the end of my series are guided and I do that so people can learn.

00:24:46But then after that, you really should start looking at your industry.

00:24:50What do you want to be?

00:24:51Do you want to work in finance?

00:24:52Do you want to work in banking?

00:24:53Do you want to work in tech?

00:24:54Do you want to work in healthcare?

00:24:56Do you want to work in this or that or this or that?

00:24:57There's so many different fields.

00:25:00So then you can build projects for those domains, right?

00:25:05You can reach out to someone who works in finance, say, Hey, if you were building a project,

00:25:08what kind of project would you build?

00:25:09Someone will answer you.

00:25:10Just message a bunch of people.

00:25:12And then you can build that type of project and cater your projects to that domain so that when somebody,

00:25:18a physical person actually does see your resume, they're like, Oh, these are projects that are related to like what

00:25:22we do.

00:25:22This is pretty cool.

00:25:23Um, I think that is, that is what I would do if I was just starting out.

00:25:32Give me a sec.

00:25:33I'm going to drink some water.

00:25:39I'm sitting very tall.

00:25:43Uh, let me see.

00:25:45Matthew's laying down the hammer.

00:25:47Stop spamming.

00:25:48All right, let's see.

00:25:53Rohit Sarna.

00:25:55In this generative AI world, investing time in data viz tools isn't important.

00:25:59It just skipped down, but you, I got, I think I got the question.

00:26:04Um, let me go back up.

00:26:08I'm going to find your, where we're at.

00:26:11Cause that was a good question.

00:26:13Um, in data, should you be investing your time in data in tools like Tableau?

00:26:19All right.

00:26:20Earlier I said, and I, I'm one of, this is like something I'm very, I'm very confident on is that

00:26:26data visualization is something that AI tools are going to be very good at.

00:26:31Um, I think they've already created a lot.

00:26:35Even before like 2023, there was already a lot of building dashboards easily.

00:26:41I think they're going to get better, especially in the dashboarding area.

00:26:44I think it's going to be something that AI is going to help out a lot with, but you still

00:26:48need to know how to do it.

00:26:50And let me give you an example.

00:26:52Right now, I've even heard examples, uh, people of using AI to create dashboards because you can create them so

00:26:59easily now, right?

00:27:00You can just bam, you know, you have the data.

00:27:03Let's just create it.

00:27:04Bam.

00:27:04You have it.

00:27:05It leads to people frivolously creating dashboards that aren't needed, right?

00:27:12So, and that's always been a problem.

00:27:14And so understanding what visualizations to create, how it should be displayed are things that you still need to know,

00:27:23right?

00:27:24Because it can generate it.

00:27:25And then you're, you may just go along with it.

00:27:27That's not good.

00:27:28They may not be the best way to do it.

00:27:29Um, so understanding those two things are really important and understanding the underlying data and how data gets visualized, because

00:27:36there's a lot of times where you have certain data and you need to pivot that data.

00:27:41You need to reshape that data to get the visualizations you need.

00:27:44And AI may just not understand the context or the exact thing you're trying to do.

00:27:49And if you don't know how to work with that data, well, then you're going to get visualizations and dashboards

00:27:54very easily with these AI tools, but they're not going to be what you need and they're not going to

00:27:58be good.

00:27:59Um, so just because AI can generate a lot of code, generate a lot of dashboards, generate a lot of

00:28:06things, doesn't mean it's good.

00:28:07You still need to know, like, what does the customer, what does the client actually need?

00:28:11What am I actually building?

00:28:13What does this data look like in the database?

00:28:15How should it look in the visualization?

00:28:17There's a lot of nuance.

00:28:18When people are first starting out, it really, I think a lot of beginners think it's, uh, going to be

00:28:26very easy now.

00:28:27But I actually think with AI, in some ways, certain things are going to get harder because you see it

00:28:32in front of you now, visually, some AI creates something and you're just like, yeah, why not?

00:28:36It works.

00:28:37Why not?

00:28:38And it's going to, it builds complacency with the actual quality.

00:28:42And so as quality goes down, AI doesn't, they don't know quality.

00:28:47They don't know what's better.

00:28:49You're supposed to know what's better.

00:28:50And so that's going to be something that I got, I'm keeping my eye on because I'm very worried about

00:28:54it.

00:28:56Um, but yeah, still need to know it.

00:28:58Still need to know it.

00:28:59Still learn it.

00:29:04Um, this is from Nikita Kim.

00:29:08I received my certificate for business data analyst, but I still don't know how to use SQL.

00:29:12That's a problem.

00:29:12I don't know, uh, what program you went through, but SQL's like, excuse me, I got something in my throat.

00:29:19Give me one sec.

00:29:22SQL is like a fun fundamental tool.

00:29:25I don't know what program would not use teach you SQL.

00:29:29If you look on like jobs on LinkedIn, like 80% of data analyst jobs are using SQL for some

00:29:35variation of SQL.

00:29:36Um, that's a, that's a miss.

00:29:37And anyways, I'm not criticizing you.

00:29:39I'm just saying that's a, that's shocking.

00:29:41Any tips for easily grasping onto SQL?

00:29:44You just got to start, um, start with downloading my SQL database.

00:29:49Downloading my SQL server database, getting data into it.

00:29:53I have tutorials for free on my YouTube channel, all about SQL.

00:29:56That's like some of my core content on my YouTube channel is SQL.

00:29:59Cause I love it.

00:30:00I think it's so important.

00:30:01Um, so I would really recommend going through those playlists.

00:30:05I have beginner, intermediate, and advanced.

00:30:07Just follow them along.

00:30:08And there's projects.

00:30:09Follow those.

00:30:10Um, I, I can't recommend that enough, but to easily grasp it, you really just need to start from the

00:30:16basics.

00:30:16Build your way up and start actually diving into real data eventually.

00:30:21Uh, that's what I would do.

00:30:25Let's see.

00:30:26I'm looking at questions again.

00:30:29Can a data analyst migrate to data scientist?

00:30:32Uh, this is from Raheem Mehta.

00:30:35Does that sound okay?

00:30:36What would be the pathway for that?

00:30:37Absolutely.

00:30:38A hundred percent.

00:30:39In fact, I considered it a while back because I was working on a data science team with data scientists.

00:30:44I, you know, I liked the machine learning stuff, not as much as the data analysis stuff.

00:30:48So I ended up not doing it, but here's what I will say is there was a lot of overlap,

00:30:52a lot.

00:30:54Um, you know, when I was using R on the data science team, they were using data, uh, a lot

00:30:59of R for machine learning.

00:31:00And I was doing a lot of data quality checks.

00:31:03I was helping, you know, structure the data for the machine learning and all this stuff.

00:31:08So if you know a lot of data analysis stuff, right, you're already deep in SQL, Excel, Python, Pandas, uh,

00:31:16you know, databases really well.

00:31:18What I would really start focusing on for data science work is the machine learning piece, right?

00:31:24That's kind of the bridge.

00:31:25That is like the next level.

00:31:26If you want to go up, uh, or over to data science, that's what you need to learn is machine

00:31:33learning.

00:31:33It's not for everyone.

00:31:35Personally, it wasn't my favorite thing.

00:31:37Um, I liked the data engineering.

00:31:41If I was going to change to anything, I liked the data engineering stuff.

00:31:44Um, which is also a good thing, uh, to look at, you know, later on, if you're thinking about doing

00:31:49that.

00:31:53I'm just reading through questions.

00:31:55I kind of like this here now.

00:31:57Now I kind of like this because I feel like the audio is better.

00:31:59And I feel like, uh, but it was above me.

00:32:01So maybe the audio wasn't as loud, but now I feel like it's next to me.

00:32:04So you should be able to hear me good.

00:32:18Uh, I don't, I'm just going to read this.

00:32:20I'm not 100% sure.

00:32:22Dijon Jalo.

00:32:22Hello, Alex, you have a KPI dashboard on your portfolio.

00:32:26I was wondering if you did a follow along for that one.

00:32:29I'm not sure where to find it.

00:32:31Um, what was the project for?

00:32:33You know, give me some, give me some information on what that KPI dashboard is.

00:32:36Cause I can't remember.

00:32:37I do have a KPI dashboard actually on, um, analyst builder.

00:32:43It's for my Tableau course.

00:32:45It is an IT dashboard.

00:32:49Very realistic to when I was a manager of, uh, analytics in IT within my healthcare company.

00:32:56Um, it's very similar.

00:32:58It's talked about churn rates and, you know, uh, it, if that's the KPI dashboard,

00:33:04you are talking about that is my, yeah, that that's a great dashboard.

00:33:08It's very realistic and lifelike.

00:33:11That is like things I used to have my team build.

00:33:13And we used to build in, uh, in my old team.

00:33:15Um, I, I think it was the Tableau course, maybe been the Power BI course.

00:33:22I don't think, hmm, maybe it was the Power BI course.

00:33:27I can't remember, but I did a KPI one of those.

00:33:31Excuse me.

00:33:32Let me get some water.

00:33:33I'm going to read questions while I drink.

00:33:42Hi, Alex.

00:33:43I'm going to study CSE, AI and machine learning course.

00:33:46We'll be a high paying job after five years.

00:33:48Um, yeah.

00:33:49Yeah.

00:33:50Knowing AI, knowing data, knowing machine learning is going to be very valuable.

00:33:57I don't, I, in my personal opinion, this idea and this notion that AI is going to be able

00:34:04to do everything and therefore make the cost of all people who work in data go lower, I

00:34:09think is incorrect.

00:34:12Um, I, I really don't believe that.

00:34:14I think that AI is going to be very helpful.

00:34:19It's going to cause a lot of competition.

00:34:21Um, but it will still be a very valuable job to know really well.

00:34:26Uh, and so knowing AI and machine learning is still very valuable.

00:34:30In fact, I've been hearing from a lot of data scientists lately, and this is purely anecdotal.

00:34:35I've had like several people reach out to me saying, Hey Alex, um, you know, I work as

00:34:41a data scientist at this company.

00:34:42We do a lot of forecasting, machine learning models, uh, predictive modeling and things like

00:34:46that.

00:34:47And we've been trying to use AI to replace what we've been doing.

00:34:51We even brought in a consultant who's supposed to be good at this, but the AI cannot get

00:34:58has a high of accuracy or, or do as good of a job as our machine learning models.

00:35:02Do you have any advice on this?

00:35:04And the first thing I said was, is no, that's not my area of expertise.

00:35:06I'm just going to tell you right away.

00:35:09But, um, you know, what I would do is if I were in your shoes is I would like really

00:35:17study

00:35:17this, I would see is, are there specific models designed for what you're doing?

00:35:23Um, or are you just using like open AI model APIs?

00:35:27And he's like, no, we're just using open AI APIs.

00:35:29And I'm like, okay, well, I would look for specific models that are very good at what

00:35:34you're looking for.

00:35:35So he messaged me back.

00:35:36This is just one example.

00:35:37And he's like, I, there aren't any out there or the ones that did, we've tried them now

00:35:41and they don't, aren't even as good as open AI.

00:35:44And he's like, the machine learning models are like significantly better.

00:35:48And so as people use AI in all areas, we're finding more and more limitations.

00:35:54Um, there may, they may get a lot better over time, but even for like data science, uh, there

00:36:01are going to be things and tools and, and ways that just are going to be better.

00:36:05And so, you know, start playing around with these things, uh, start getting into AI and

00:36:11machine learning and data science and data analytics and just data in general, it's going

00:36:16to be a valuable skill.

00:36:17I don't see it, uh, changing any time soon.

00:36:21Paradox pages, what AI agent tool will you recommend for data analysis?

00:36:27Um, I mean, there's a lot of good ones out there.

00:36:30I think, you know, using tools like I'm, you said agent, but I think using tools like

00:36:37cursor and get hub co-pilot, you can use agents on, you know, a lot of different just AI platforms

00:36:42now are good to know and know how to use and do.

00:36:46Um, but just open AI chat is a great one.

00:36:50Uh, Claude is very good for certain things.

00:36:53They're all going to have their kind of different flavor and things they're good at.

00:36:56Um, but it's one that makes sense for kind of your workflow, I guess.

00:37:01Um, this is another one from Swayam Tawari.

00:37:05Quick question, Alex, is business analyst a good career step after graduating in IT and

00:37:10doing master's in business analyst course?

00:37:13Um, I think that business analyst is going to still be a useful job.

00:37:17It's very interactive with clients.

00:37:20So when I was on a team, we hired, we, I was on a hiring team.

00:37:23I was just a data analyst, but I was on the hiring team.

00:37:25We hired a business analyst, um, and we had a business analyst already on the team.

00:37:29But when we were hiring, we were like, Hey, listen, you're not going to be doing a ton

00:37:32of the data stuff.

00:37:33You'll be working a little in SQL and Excel.

00:37:35And we need you to know that, but you're going to be mostly interfacing with the other

00:37:38departments in the company and interfacing with our clients.

00:37:43That's what a lot of, so you need a technical mind, someone who understands data to be able

00:37:47to talk with the clients well, and then interpret it for the team.

00:37:51And that's what a business analyst typically does.

00:37:53Um, so yeah, there's still going to be used for that, especially at larger companies.

00:37:57Oh, thank you, Matthew.

00:37:58Matthew plugged my, uh, my LinkedIn, uh, link.

00:38:01You didn't have to do that.

00:38:02I really do appreciate that.

00:38:03Cause, uh, yeah, go follow me on LinkedIn.

00:38:04I post some, you know, I think useful stuff every so often.

00:38:10Um, this is a good question.

00:38:13This, this one is a good one.

00:38:14I think people need to hear this one.

00:38:18All right.

00:38:19What time is it real quick?

00:38:21934 doing great on time.

00:38:23Excuse me.

00:38:24Hi, Alex.

00:38:25This is from, um, Tiami Obasanjo.

00:38:31Hi, Alex.

00:38:32Could you advise on how to get mentors as a new data analyst?

00:38:35Looking back at my career, I've had such good mentors, um, in my life that really progressed

00:38:43my career immensely.

00:38:45So I can't recommend getting a mentor enough.

00:38:49Um, someone to kind of, who knows more than you can kind of give you a path and a direction.

00:38:54Um, here's what I would say.

00:38:56If you are looking for someone who can do that, you need to start making connections.

00:39:02You need to, you have to, you cannot find a mentor unless you're paying for it.

00:39:07You cannot find one.

00:39:09Um, that's just going to help you unless you make a connection.

00:39:11That means reaching out to people that could be via email.

00:39:15Cause I've mentored people via email.

00:39:17Um, that could be, excuse me.

00:39:21That could be on LinkedIn.

00:39:22That could be on any way you want to find people.

00:39:25It could also be joining local groups, um, in your community where they have a meetup,

00:39:31a tech meetup, however you want to do it.

00:39:33But you need to build relationships.

00:39:35Um, and that is a tough thing when you're first starting out, but you have to be inquisitive.

00:39:40You have to keep at it.

00:39:42You have to put in effort.

00:39:43Um, there are mentorship programs.

00:39:45I myself used to have a mentorship program.

00:39:47I mentored like 200 plus people, um, on, and I did it like super cheap.

00:39:51I was like, uh, I think I was dang near losing money on this.

00:39:57I used to do that.

00:39:58Uh, I didn't have enough time to, cause I eventually had like a, uh, backup.

00:40:03I had a, what's it called?

00:40:06I had so many people reaching out to it.

00:40:08I put them on a list and my list was immensely large, um, to where I was like, all right,

00:40:14I got to do something about this.

00:40:15That's why I created the analyst builder.

00:40:17Um, and so I don't do mentorships anymore, but there are people out there who do mentorships

00:40:22and you can pay for it too.

00:40:23Still is helpful.

00:40:27All right, let me go.

00:40:28Let me look.

00:40:32All right.

00:40:33This is a great question.

00:40:34Shu Bon car.

00:40:36Hey, Alex, since entry-level data analysts and business analyst jobs are very saturated

00:40:40and extremely competitive, what are some other job opportunities I can explore?

00:40:43I am someone who loves business intelligence and machine learning.

00:40:47Uh, I don't disagree.

00:40:49I think right now we have layoffs cause the economy, mostly the economy, I would say like

00:40:5495% of layoffs right now are purely for economic reasons.

00:40:59Stocks, uh, uh, they don't want their stocks to go down.

00:41:02They want their profits to stay high.

00:41:04I think it's, that is my genuine take on it.

00:41:07I think some jobs, especially in like, um, customer service and, uh, certain other roles

00:41:14that AI is actually taking away some of those jobs, but in data, I, I think most of them

00:41:19are, are the economy.

00:41:20So we are having layoffs.

00:41:21Then we have an influx of people who are wanting to get into just tech and data in general because

00:41:26of the prestige or the money or, you know, the curiosity, they, they, they want to work

00:41:32remotely or whatever it is.

00:41:33It is very alluring to a lot of people.

00:41:35So how do you, how do you, uh, kind of break in?

00:41:38How do you make yourselves competitive?

00:41:39How do you look for other opportunities?

00:41:40Here's what I'll say.

00:41:42Most people are looking for jobs remotely.

00:41:47And there was a great video.

00:41:48I don't have the video on this, but, um, another tech YouTuber, data YouTuber, I cannot remember

00:41:56who made this video.

00:41:57If I did, I would, I would let you know.

00:41:59They made a, a, a video on job applications for local versus remote jobs.

00:42:05And you can only imagine that the remote jobs had like, it was like 10 times more, uh,

00:42:13applications than any local job, of course, because local jobs are local.

00:42:19They're not going to be as competitive.

00:42:21One of my biggest suggestions to almost everybody is in, and this isn't possible for everyone

00:42:28because some people can't do this, but one of my biggest things is to look local, look

00:42:33at local jobs, local businesses, local companies.

00:42:36Uh, if you have the ability going to metropolitan areas is a huge bonus.

00:42:43I mean, massive local, like when I was living out in Dallas, one of the best job markets to

00:42:50be in a local market because people want to hire locally.

00:42:53They want someone who can come in and be in person.

00:42:56And so that is a giant advantage.

00:42:58And if you have that ability, I highly recommend it.

00:43:00But, um, only applying for remote jobs can be very tough, very tough.

00:43:05Even if, for me, if I was to apply for just remote jobs right now, it'd be tough for me.

00:43:09I'm not even lying.

00:43:10That's, that's the truth.

00:43:11Just, um, it's just tough for only remote jobs, but there are so many jobs out there.

00:43:17There are still a ton of jobs out there.

00:43:20They just, it's hard.

00:43:22If you're looking at only remote, that's like 10% of jobs out there that are purely remote.

00:43:26So you have 90% of people applying for 10% of the jobs.

00:43:30It's not, not good math right there.

00:43:32It's not good odds, uh, but good.

00:43:34Very good question.

00:43:39I'm looking at questions.

00:43:41Give me a sec.

00:43:43Jigs.

00:43:44Hi, Alex.

00:43:45I'm confused how to start.

00:43:46Which one of the beginner videos?

00:43:47I do.

00:43:48I have so many videos.

00:43:49Look at my data analyst bootcamp.

00:43:52It starts with the exact, it's progresses in the exact skills I would learn progresses

00:43:57from inner beginner up to advanced.

00:44:00And then I have projects throughout.

00:44:02At the end of the data analyst bootcamp, I walk you through, um, you know, how to build

00:44:07a portfolio, how to build a resume, how to apply for jobs, everything for free.

00:44:11My data analyst bootcamp on YouTube.

00:44:13That's what I would do.

00:44:15Best place to start.

00:44:19Allian Emre Tunk.

00:44:20Hey, Alex.

00:44:21I got a, I got a freelance data.

00:44:24I got freelance data projects.

00:44:25I'm using many of the things I learned from you.

00:44:27Wanted to thank you.

00:44:28Oh, that's awesome.

00:44:29I thought you were going somewhere.

00:44:30I didn't read the whole thing.

00:44:31I thought you were going somewhere different with that, but that is awesome.

00:44:33Uh, congratulations.

00:44:34I hope that, um, the freelancing work is really good for you.

00:44:38You can build on that and, and, you know, get some clients from that.

00:44:41That's what I recommend.

00:44:42People who are doing freelance, you know, sometimes it's just one-off little jobs, but

00:44:46do that project and then follow up with them in a few weeks, follow up with them in a month.

00:44:52Some will say no, but some might be, oh, actually, yeah, we do have another project that you'd

00:44:55be helpful on.

00:44:56So, uh, you know, that's how you can start like a full-time thing, you know?

00:45:08Um, I, sorry, I'm reading a question, but I don't really understand it.

00:45:13All right, guys, we got about 10 minutes.

00:45:15In 10 minutes, I'm going to do, I'm going to create some codes that people can apply

00:45:20at the checkout for courses on Analyst Builder.

00:45:22In order to do this giveaway, you have to have an Analyst Builder account and you have to

00:45:27go to the pricing and select a course that you want, and I'm going to give you the code.

00:45:30I don't want you to buy anything that's not what I want you to do.

00:45:33I just want you to be able to enter the code to get it because there will be people in

00:45:38here who are going to get that code.

00:45:39They're going to use it.

00:45:40They're going to get a free course.

00:45:40And that's what I'm hoping to do, but I want everyone to have a chance.

00:45:44What can I do to stand out?

00:45:46I've been learning SQLs, have low Python, Excel, and Pandas.

00:45:49I've been creating dashboards, using real world projects focused on companies I apply

00:45:52to.

00:45:52What else can I do?

00:45:53Tyrone Williams.

00:45:54Great question.

00:45:56When I think of, when I think back, and I haven't hired for like two years, back when

00:46:03I was on a hiring team and I was a hiring manager, here are the things that stuck out

00:46:07to me.

00:46:09One is someone who their resume is tailored to an industry.

00:46:15I can tell if this is just a very generic data analyst resume that you're applying with

00:46:22for a thousand of them, or you're like, oh no, I want a healthcare job.

00:46:26And that sets off alarm bells in my head.

00:46:28I'm like, oh, that's a good thing because I need someone who understands healthcare.

00:46:32And that's the same for any other domain, right?

00:46:34If you're in banking and you're working on, let's say, overdraft fees and you're trying

00:46:41to analyze overdraft, you know, someone who knows banking already, that's a, that's a

00:46:45good candidate.

00:46:46And so my recommendation is make four or five different resumes, four different industries

00:46:53that you are wanting to target.

00:46:54Maybe it's just two, maybe it's just finance and healthcare.

00:46:56Just for example, make two separate resumes.

00:46:58If it's a finance job in finance, use the finance resume.

00:47:02If it's not, use this resume, maybe create two separate projects or separate projects for

00:47:07each of them that will help you stand out.

00:47:10And, you know, those keywords on things like, you know, in healthcare, claims data, insurance,

00:47:20I don't know, just random keywords, ICD codes, the project in the project description in your

00:47:26project section has, you know, I work with CPT and ICD codes.

00:47:30Those things stand out.

00:47:32I have hired people based off of those things that helps people stand out.

00:47:36I promise you, it just takes more effort, takes more time.

00:47:42All right, let me see.

00:47:49Yeah, Matthew is right.

00:47:51I'm way up in the chat.

00:47:53I don't answer chats right when they get asked because there's so many questions I have to,

00:47:56you know, I have to catch up.

00:47:58It takes a while.

00:48:00It takes a while.

00:48:02Um, let's see.

00:48:05I'm catching up though.

00:48:07Um.

00:48:11I don't, I'm just going to read as an interesting question.

00:48:13Hey, everyone.

00:48:14Hi.

00:48:15That's a, that's the name.

00:48:16I'm working as a petroleum engineer working in the petrophysics.

00:48:20So we have a lot of data to do projects on.

00:48:22Do you recommend me learning data analysis?

00:48:25Uh, I do.

00:48:26I mean, if you have a lot of data in your area and you start knowing how to use that

00:48:31data,

00:48:31uh, the company all of a sudden is like, holy crap, this guy or girl, this guy is really

00:48:39helping us.

00:48:40That's super valuable.

00:48:41And then you're like, yeah, but you know, I've just been doing it for free.

00:48:46I think if I want to continue doing this useful analysis of the data, I might need a promotion.

00:48:53And bam, instant promotion.

00:48:56I'm, I'm just joking, but that is one of the best ways to get into data is out of a

00:49:00need.

00:49:00You see the need, you have all this data, but no one's doing anything with it.

00:49:04And then you start all of a sudden breaking it down and categorizing it and doing some

00:49:09analysis and you know, whatever you're doing with it, that's valuable.

00:49:12That is adding value to your company.

00:49:14And they're going to appreciate that.

00:49:15Um, most of the time, sometimes we're just like, ah, it doesn't matter.

00:49:17But if you actually do find something useful, a pattern, uh, some type of issue in the data,

00:49:24that's a great thing.

00:49:25That's a great thing.

00:49:33Just, uh, looking.

00:49:37Uh, Ikaj Kumar, for someone who doesn't have any experience in data analysis or MIS is 28

00:49:44too late to start a career in data analytics.

00:49:48Uh, no, 28 is not too late to start.

00:49:51Definitely not.

00:49:52Now, if you were like 65, ooh, that'd be a tough sell.

00:49:58You know, that's a near retirement age, but, uh, no, 28 is not at all.

00:50:03I've worked with so many people in the data space who didn't start working until they were

00:50:0935 in data or 40 in data because they saw a need, right?

00:50:13They were doing this job and then all of a sudden they had all this data, but no one

00:50:17knew what to do with it.

00:50:17Just like that previous example from high, everyone high.

00:50:20I think it was, the name was, that is an example of people who then broke into that data part

00:50:24of their job and they loved it.

00:50:26And then they start doing it.

00:50:27They're like 40 years old, 50 years old.

00:50:29So absolutely not too old.

00:50:36Let me see.

00:50:42Taki, thank you for joining.

00:50:45Taki's not his real name, but thank you for, uh, thank you for joining.

00:50:48It doesn't matter if you're late.

00:50:49We got just a few more minutes and I'll start doing a giveaway.

00:50:52Uh, let's see.

00:50:54Is Christine in here?

00:50:55Did I miss it?

00:50:58I saw Matthew say at Christine Freeberg.

00:51:00Oh, there she is.

00:51:02That's my wife.

00:51:04She has a YouTube account, but I don't think she posts videos yet.

00:51:08Maybe she's going to, maybe she will.

00:51:12She'll post videos.

00:51:13She'll, she'll become one of those, uh, uh, content creators.

00:51:17That's like what it's like to be married to an influencer.

00:51:21I wouldn't consider myself an influencer, but that'd be hilarious content.

00:51:25Cause my, my everyday is quite boring, but she should start making videos.

00:51:33Maybe if enough people go follow her or subscribe to her channel, then she'll do it.

00:51:38All right.

00:51:38Let me see.

00:51:39I'm just going to take a few more questions.

00:51:41Um, I do this every week.

00:51:43I do this every week, every Thursday.

00:51:45I'm probably going to do this hopefully towards like mostly towards the end of the year.

00:51:49We'll see.

00:51:50Um, but every week I'm going to be doing this.

00:51:52So if I didn't answer your question, come back next time.

00:51:54All right.

00:51:54Let me see.

00:52:01I'm just looking.

00:52:01I'm just reading.

00:52:02I went to, it skipped down to the bottom.

00:52:04So now I'm looking at the most, some of the most recent questions.

00:52:12And Sandra said, so true.

00:52:13Solving that industry's problems is key.

00:52:15It 100% is.

00:52:17Um, and a lot of times people don't slow down to look at the data.

00:52:21They just go, go, go, go, go all into intuition and legacy thinking and, and all these things

00:52:25that they don't stop and actually look at the data.

00:52:27Um, and if you stop and look at the data and maybe it's not even part of your job, but

00:52:32if you stop and look at it and you start using it, you know, that it proves helpful.

00:52:36They're going to start rethinking.

00:52:37Oh, maybe, you know, John really should be doing this more.

00:52:41Cause that was really helpful.

00:52:45Bam.

00:52:46Senior data analyst.

00:52:49Um, I've been looking at questions.

00:52:58Some of the questions I've already answered, so I'm not answering them again.

00:53:00Some of them, I just don't understand.

00:53:02So let me see if there's any more that I need to answer before, uh, before we head out.

00:53:10Is there anybody I can recommend for mentorship?

00:53:12Um, I don't, I don't know anyone that's doing data analytics mentorships at the moment.

00:53:19Uh, off the top of my head, at least.

00:53:21I know people are doing other types of mentorships or different types of programs, but I don't

00:53:25think it's specifically for data analysis.

00:53:28Okay.

00:53:38I'm just reading.

00:53:39Um, bum, bum, bum, bum, bum.

00:53:49Um, all right, I've answered.

00:53:52So I see people.

00:53:53Let me go to the very bottom.

00:53:54Maybe someone has asked a new one.

00:54:00All right.

00:54:00This will be my last question.

00:54:01Um, this will be my very last, uh, very last question.

00:54:11Uh, Shubankar.

00:54:12I think you asked a question earlier.

00:54:13Is it possible to be promoted to a data scientist from a business analyst role or will I be promoted

00:54:18to a BI analyst role first?

00:54:20Um, business analyst would be more difficult to go to a data science position because data

00:54:25science is quite technical.

00:54:26And typically business analysts aren't as technical.

00:54:30Um, and so I would probably try to get into a data analyst role and, or like you said,

00:54:37uh, a BI developer role or a BI analyst role where you can get more hands-on with data and

00:54:43get, be more technical before.

00:54:45If you do want to go into data science, then maybe learning some machine learning on the

00:54:50job or, or later, uh, or in your free time to upskill into machine learning.

00:54:56That's what I would do.

00:54:58That is what I would do.

00:55:00All right.

00:55:01I answered as many questions as I could.

00:55:03Now we're going to go to the giveaway.

00:55:05All you need to do is go to, there's a link in the description.

00:55:09I think somewhere, all you need to do is go to analystboulder.com.

00:55:13That is my platform for learning has all my courses as my technical platform where you

00:55:18can learn, uh, to code, you have to have an account.

00:55:21So sign in, I'm going to go there right now.

00:55:23I'm not on the screen, but I'm just going to walk you through.

00:55:25So go to analyst builder.

00:55:26You have to sign in, go to pricing.

00:55:29You don't have to buy anything.

00:55:31I'm not trying to get you to buy anything, but then go to courses.

00:55:34These are all of my courses.

00:55:35Um, so, you know, I have, um, I have my data analyst bootcamp.

00:55:40If you want to go like way more in depth, I have these courses, these courses go way more

00:55:45in depth and they cover more things than, you know, on YouTube.

00:55:48Find the course you want.

00:55:50You click on buy, but you're not buying it.

00:55:52I'm not trying to get anyone to buy anything right now.

00:55:54I promise you.

00:55:55I'm, I'm really not just go say, I want, oh man, uh, this getting GitHub for data professionals

00:56:02course.

00:56:03I'm going to buy it.

00:56:04Now don't buy it.

00:56:06There is an ad promotion code, ad promotion code.

00:56:15Okay.

00:56:19In that ad promotion code.

00:56:24I'm going to give you a code.

00:56:27Give me one sec.

00:56:28I'm getting over there.

00:56:33Let me go here.

00:56:35Let me go here.

00:56:37All right.

00:56:38I hope you're ready by now.

00:56:39I'm about to make the code.

00:56:41I'm about to do it.

00:56:43All right.

00:56:43This first code, only one person is going to get it.

00:56:45So if you get it, you're going to apply the code.

00:56:48It'll go down to $0 and then you click buy.

00:56:52That's it.

00:56:53You have to be the first person to buy the zero.

00:56:56When it goes down to zero, click buy.

00:56:58If it gives you invalid or, or an issue, that means that, uh, someone else got it first.

00:57:03Um, all right.

00:57:05The first code, something we talked about a lot today.

00:57:09Uh, the first code is AI, all caps, AI.

00:57:14That is the code.

00:57:16Um, the second code, two people are going to get, and I'll do the next one for two people

00:57:21as well.

00:57:22Uh, this is the name of my wife.

00:57:24So if you know my wife's name, you can type that in two people.

00:57:28We'll get that one.

00:57:29I'll give you a hint.

00:57:31Uh, her name is Christine and it's all caps.

00:57:33Uh, wasn't a hint.

00:57:34I just gave you the code.

00:57:35All right.

00:57:35Let's let me see real quick.

00:57:37Let me see if someone's already gotten the AI one.

00:57:40I just have to refresh.

00:57:45All right.

00:57:45Someone got the AI one.

00:57:47Awesome.

00:57:47If you got one of the courses and you see it, you go to your purchases tab, you'll see

00:57:52it in your purchases.

00:57:53If you got it, let me know which one you got.

00:57:56Cause I'm always curious as to what, uh, to what people got, you know?

00:58:03All right.

00:58:05The last code that you need to put into the, uh, code section is the very last code.

00:58:12And there's two people can get this one as well.

00:58:15Um, this is just going to be, let me see.

00:58:19I'm going to throw you for a loop.

00:58:22Uh, yeah.

00:58:24This is the name.

00:58:26I don't know if I did this one before.

00:58:27This is the name of our, my newest dog.

00:58:30She made it on the live stream.

00:58:32Last live stream.

00:58:33She's a cute little mini dachshund, little brown, little mini dachshund.

00:58:36All right.

00:58:37People already got the Christine code.

00:58:38That one's gone.

00:58:39And the last one is Penny.

00:58:41Penny is the name.

00:58:42It's all caps.

00:58:43Penny is the name of our newest dog.

00:58:46She's very cute.

00:58:47Very cute.

00:58:48Let me see if I can pull up a picture of her.

00:58:51I'll show you.

00:58:56Oh, that's a good photo.

00:58:58Look at her go.

00:58:59All right.

00:59:00Let me get over here so I can make sure I'm showing you.

00:59:03This is Penny.

00:59:08There it is.

00:59:09Hi, Penny.

00:59:11Oh, she's so cute.

00:59:13That's Penny.

00:59:15She's our newest dog.

00:59:16We now have three, believe it or not.

00:59:18Oh, my Lanta.

00:59:22Look, the wife just wants more dogs.

00:59:24I can't say no forever.

00:59:26We may have four or five by the end of the year.

00:59:30But thank you guys, everybody, for coming.

00:59:32That's the live stream.

00:59:33I hope everyone got it.

00:59:34If you did get one of the courses, let me know.

00:59:36Oh, Krishna said, I got the Azure and AWS Cloud Essentials one.

00:59:40That one is such a great course.

00:59:43It is so, so good.

00:59:44I'm glad you got that one.

00:59:50All right.

00:59:52Modest Auto said, just got the MySQL interview crash course.

00:59:56Using your wife's name.

00:59:57Alex, you're the best.

00:59:58Thank you for doing these videos each week.

00:59:59Awesome.

01:00:00I hope that one is really good.

01:00:01That one is specifically geared towards interviewing.

01:00:04All right.

01:00:05So getting ready for interviews.

01:00:06At the end, it goes through general technical questions like, tell me what you know about SQL.

01:00:10You know, those are general questions.

01:00:12Those aren't the coding questions.

01:00:14Um, and then you can also practice those questions in our general technical questions, uh, section.

01:00:22And so, uh, pretty, pretty cool.

01:00:27All right, guys, I'm going to see you guys next week.

01:00:29I will do it at the same time.

01:00:31Wow.

01:00:31Wait a second.

01:00:32I might be out of town.

01:00:34No, I think we're leaving Thursday afternoon.

01:00:35We're going to visit my wife's family.

01:00:37So we're gone.

01:00:38I think Thursday night.

01:00:40So I think Thursday at 9am will be, but just make sure if you want to be there.

01:00:45Um, if you want to be in that live stream, just check out when I post it.

01:00:49Cause I'll post it like on Monday and then you'll know what time it is and I'll post it on

01:00:53social media.

01:00:54All right, everybody.

01:00:55I am out of here.

01:00:57Thank you guys for joining.

01:00:57I'm ending early today.

01:00:58That's like the first time I've ever ended early.

01:01:00Um, but thank you guys for joining.

01:01:01I really appreciate it.

01:01:02I hope that answering these questions was helpful.

01:01:05Um, if it was, be sure to come back next time.

01:01:08If you have any more questions.

01:01:10All right, guys, I'm out of here.

Alex The Analyst Q/A Livestream | Come Ask Me Anything

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