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David spent 13 years in architecture before switching to data. He landed his first data job in about 90 days.
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β TIMESTAMPS
00:00 β 13 years in architecture
06:00 β The internship
08:39 β Study on your own time
14:24 β Networking pays off
21:24 β Advice if you're on the fence
π CONNECT WITH DAVID
π€ LinkedIn: https://www.linkedin.com/in/davidnkovacs/
π CONNECT WITH AVERY
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I guess, did anyone think you were kind of crazy for
2
:leaving this architecture career?
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:'Cause you had worked in architecture
for what, like 12, 13 years-ish?
4
:David Kovacs: Data analysts are
just gonna be replaced with AI,
5
:and the market is saturated.
6
:Then I was DoorDashing between my
old job and finding my new job,
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:hitting the program hard, studying.
8
:I'm living proof of that.
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:Avery: What does it actually look like
to go from, you know, architecture
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:and landscape design to data analyst?
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:All right, David, take me back before
you were a data analyst into this
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:architecture and landscape design life.
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:What did that career look like?
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:What were you actually doing?
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:David Kovacs: Uh, yeah, so I
went to, uh, college for, it's
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:called architectural technology.
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:Uh, really just a fancy way of
saying architectural drafting.
18
:So my day-to-day looked like
finishing red lines for project
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:managers and filling requests.
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:Not quite the creativity that I
was looking forward to when I went
21
:to school for it, but that's kinda
what my day-to-day looked like.
22
:Avery: Okay.
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:David Kovacs: Th-
24
:Avery: I- maybe I'm sensing this
wrong, but that sounds like you maybe
25
:got kind of bored just doing that- Mm
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:and it wasn't, like, super
fulfilling necessarily.
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:David Kovacs: Eventually, yeah.
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:Yeah, boredom kicked in, for sure.
29
:Avery: Yeah, and that makes sense.
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:I mean, that's how I was as
a chemical lab technician.
31
:Um, you did have the chance to work
on $140 million, uh, baseball stadium.
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:What were you designing for them,
and I guess, where was that at?
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:David Kovacs: Yeah, again, just filling
the orders of the project managers
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:and it's actually about 25 miles
down the road from where I live, so
35
:I took my, uh, my wife and my in-laws
to go see it this past weekend.
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:That is one cool thing about being in
architecture for so long and actually h-
37
:seeing projects come to life and getting
to, like, go visit them and stuff.
38
:Avery: You can be like, "I
drew lines on that," and it
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:eventually- β¦ came to, to life.
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:Um, I guess at one point did you, like,
realize, "Okay, I no longer want to
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:be, you know, an architect anymore"?
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:David Kovacs: Ooh.
43
:Really my whole career was a struggle
of, like, just wondering if I'd made
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:the right decision, even in college.
45
:You know, I thought about changing in the
middle of it and I just kind of, I guess
46
:you could say I white-knuckled my way
through college 'cause I just wanted to
47
:get done with it and start some kind of
career and- There was definitely a lot of
48
:struggles over the years, job losses, so
it's been something I played around with
49
:a lot over the years, and just recently,
last year, kind of personal situation
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:with my wife being diagnosed with stage
two breast cancer kind of kicked it
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:into gear again that I just wanted to do
better for myself, better for my family.
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:Avery: It's really impressive, um,
and really a- admirable of you.
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:Yeah, uh, amazing.
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:I was gonna ask, like, what, at what
point was, you know, the tipping
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:point for you, but obviously that,
that was the tipping point for you.
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:Um, I guess did anyone think
you were kind of crazy for
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:leaving this architecture career?
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:'Cause you had worked in architecture
for what, like 12, 13 years-ish.
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:David Kovacs: Yeah, I got, uh, definitely,
uh, some comments about, oh, data analysts
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:are just gonna be replaced with AI, and
the market is saturated, and it's not
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:a good idea for you to do that, but I
think the data out there says otherwise,
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:that analysts are still getting hired.
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:I'm living proof of that.
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:Avery: I would agree.
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:Um, okay, so you didn't listen to
them, and you're like, "I'm still
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:gonna pursue this data analytics."
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:Um, why in data analytics in particular?
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:Like, what drew you to data
as opposed to architecture?
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:David Kovacs: Right, so I did a lot
of kind of exploring and searching
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:when I decided it was finally time
to leave my career in drafting.
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:Um, I found your YouTube channel, you
know, listened to how passionately you
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:speak about your own career and listened
to other data analysts speak about how
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:passionate they are about that business.
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:Avery: That's, that's super cool to
hear that it was, it was via YouTube.
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:So were you doing, like, a lot
of research via, via YouTube?
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:Like, looking up different careers like
cybersecurity, I don't know, project
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:management, those types of things?
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:David Kovacs: Yeah, I kind of, like,
did the search of, you know, careers
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:that, careers that you can get into
where you either don't need a degree
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:or your degree is relevant to the
job that you're going to be doing.
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:Um, web development is another path I went
down for a little bit as for deciding.
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:It wasn't for me.
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:I even took a career assessment,
and, like, three or four of my
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:top 10 results were some form of
data analyst, so it was pretty-
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:Avery: So you're like-
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:β¦ David Kovacs: obvious that
I should pursue that more
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:Avery: Oh, perfect.
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:That's, that's great.
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:Um, okay, so you, you kind
of do some research online.
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:You learn about data analytics.
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:Um, you watch some YouTube videos.
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:Um, obviously architecture, you know,
the tools you're using in architecture
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:are a little bit different than the
tools you'd be using as a data analyst.
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:What was, like, the first thing,
like, you, you did to, like, learn
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:data analytics, and how did that go?
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:David Kovacs: Yeah, again, just
watching a lot of videos and tutorials.
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:Um, I did do the Google certificate
in my free time while we were-
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:Avery: How, how was that experience?
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:David Kovacs: It was good.
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:I feel like it definitely gave
me a, like a peek into the world
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:of what a data analyst does.
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:I don't feel like it got
me quite all the way there.
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:It was just really- I would say
it's that first- It was just really
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:scratching the surface, you know.
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:Avery: 100%.
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:It's, it's kind of a, a very, uh,
not, not deep, uh, very shallow intro-
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:introduction to analytics in general.
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:Um, okay, so then, then I'm curious here
because, uh, you end up β¦ You know,
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:you're doing the Google Data Analytics
certificate, and then you join my
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:program, the Data Analytics Accelerator.
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:And obviously I don't have, like, a magic
eight ball to, to what's going on in your
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:life and, you know, what's going on with,
with your brain and what's going on with
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:what you're thinking, but we all leave
traces of ourselves on the internet.
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:So my marketing data tells me that you
first visited my website coming from
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:Instagram, which is, I think is really
interesting because I don't really do much
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:with Instagram currently at the moment.
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:And then 100 days later, you revisited the
website after coming from a YouTube video,
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:and you end up, you ended up joining.
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:So I'm just curious, kind of like
what happened, if you can remember in
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:those 100 days, what made you end up
deciding, you know, "Okay, the Google
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:Data Analytics certificate, it was a
great start, but it's not enough for me.
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:I want some more"?
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:David Kovacs: Oh, yeah.
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:I, I had been watching you for a while
and followed you on all platforms and,
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:and yeah, I think I, um, I just wanted
to learn with a community and, you
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:know, get help and job hunting and-
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:Avery: Um, now when you, when you
were in the boot camp, you actually
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:ended up doing an internship, and
I think that was just this, this
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:last quarter, like our, our January
internship with the UK housing data.
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:I'm curious kind of what that
experience was, was like for you.
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:Uh, I guess tell about, like, whatβ¦
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:how big was your group and what
kind of tools you guys used and
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:how that whole process was for you.
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:David Kovacs: Yeah, so theβ¦
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:I think the day after I signed up
for the Accelerator, I had learned
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:that you guys offer an internship,
and I kind of wrote Isaac.
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:Shout out to Isaac.
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:And asked, "Hey, am I too
late to join this internship?
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:'Cause I'd really like to do that."
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:And he said, "Not at all.
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:I'll put you in group seven."
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:And, you know, we did our first meeting.
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:I kind of became the, uh, business
intelligence portion of the project, where
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:I did, you know, charts and dashboards.
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:It was a really good learning experience.
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:W- was definitely very hard, 'cause you
have four or five brand-new data analysts
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:who are all learning with you, and we're
all in different parts of the world.
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:I think we had somebody in every time zone
in America, and then somebody in the UK.
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:So we were getting up at, like,
6:00 and 7:00 in the morning to,
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:to do virtual meetings and talk
about where we go from here.
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:But it was definitely worth it, and
I think it did make a difference
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:in getting the job that I have now.
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:Avery: Very cool.
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:Were, were you guys
using a lot of Tableau?
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:I, I think, like, I remember group
seven using a decent amount of Tableau.
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:David Kovacs: Yep.
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:That was us.
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:That was me.
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:Avery: Awesome.
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:Okay, perfect.
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:That was you.
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:Great.
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:Yeah, I do remember group seven
doing, um, doing some good work.
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:Um, yeah, and talk a little bit
more about, like, how it, how you
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:feel like the internship might
have helped you, uh, land the job.
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:Um, one thing I noticed is,
you know, I haven't seenβ¦
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:I don't think I've seen your, your resume
maybe, maybe in a while or a l- ever.
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:Um, but I know on your LinkedIn you
have that you were a data analyst
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:intern for my company, Snowdata Science.
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:So I'm assuming that was on your
LinkedIn when you were applying for jobs.
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:David Kovacs: Yeah.
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:Avery: Okay.
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:And did it pop up in the interview
at all, or did they ever ask
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:you, like, what you did at that,
you know, at Snowdata Science?
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:David Kovacs: Hmm.
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:Yeah, it did pop up in the interview.
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:Yeah, and they wanted to
hear from you as a reference.
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:Avery: That's, that's what
I was actually gonna ask.
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:Um, the company that you ended up
landing this role with, is that
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:the company that I, I talked to via
email about the reference stuff?
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:David Kovacs: Yeah, it is.
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:Avery: Okay, awesome.
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:Okay, so it did play a, a decent part in
the interview process- Yeah β¦ because,
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:you know, they wanted to hear a little
bit more what you did as, as an intern.
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:Um, okay, that's awesome.
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:I'm glad to hear, uh, plus
one for the internship.
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:Uh, our next- we're trying
to do four of those a year.
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:So, um, we're only at one, so we gotta
t the next one pretty soon in:
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:Um, I'm curious, like, you know,
you were still working while
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:you were doing the boot camp.
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:Is that correct?
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:David Kovacs: For a few weeks I was,
and then a situation arose at my job
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:where I had to leave, so I actually,
uh, finished up my two weeks at my job
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:and then I was just DoorDashing between
my old job and finding my new job.
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:And- I wanna talk more about that β¦ over
the evenings, yeah, and then over the w-
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:evenings and weekends I was, you know,
hitting the program hard, studying.
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:Avery: That's absolutely
amazing and really admirable.
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:I think I'd be very, I think I'd be
very stressed out in that situation.
199
:Mm-hmm.
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:But I think a lot of people are in a s-
in a similar situation where, you know,
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:maybe they're doing gig work right now
and they're trying to land a data job.
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:Um, can you just tell me more about,
like, what your day-to-day looked like?
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:Like what time, like, w-
what time were you studying?
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:Was it in the evenings or in the mornings?
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:What did the w- day in the life
look like of someone who know, who
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:was, you know, doing these gig works
while trying to land a data job?
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:David Kovacs: Yeah, you just find
moments during the day to study
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:whenever you have free time.
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:So I was out there, like, during peak
hours, you know, making deliveries.
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:Mm.
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:I'd, I'd come home and keep going through
the program, keep building projects.
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:Avery: That's super interesting to hear.
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:I'm gonna indulge myself in
a, in a selfish question here.
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:David Kovacs: Yeah.
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:Avery: Um, because you know,
one of the things I try to do in
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:the Accelerator is I'm like, you
know, people are busy, you know?
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:And not everyone has time to go through,
uh, a 12-week full-time boot camp.
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:Still try to make it fast, like
you can do it in, like, 12 weeks.
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:I think you were about, from, from
when you joined to when you landed your
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:job, I think you were about 90 days.
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:Um, ish.
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:Um, so obviously it's possible to do still
part-time, but I also try to, like, cater
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:to people who have busy lives by making
the material as available as possible in
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:as many different avenues as possible.
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:So, you know, a lot of our lessons will
have a video lesson, um, but there's
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:also the text version with pictures
down below, and we try to do, like, the
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:member only podcast, which is kind of
like the audio companion for each one
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:of the modules we have in the program.
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:We have, like, an audio
version of the module kind of.
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:I'm curious, and, and also we have,
you know, all of our, our community and
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:also all of the lessons are on an app.
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:I'm just curious, were you using,
like, any of, any of that, like, on
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:your phone, like, while you were in
the car, like, listening to member
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:only podcasts or, like, maybe you were
waiting for your next order, like,
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:you did some of the lessons on your
phone, or was it mostly at your desk?
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:David Kovacs: Oh, yeah, definitely.
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:When I was out driving around, I
listened to just about every episode
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:of the podcast, both, well, one
on Spotify and the members only.
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:Did a lot of passive learning
while I was out on the road.
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:Avery: Awesome to hear.
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:I'm super glad to hear that because
you, you create this thing and you're
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:like, "I think this is gonna be
useful for people," but you don't
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:always hear how people are using it.
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:So, um, I'm super excited to, to
hear that it was useful for you.
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:Um, I'm curious, like, what you thought
was maybe the hardest part about landing
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:a data job in general and, and maybe in
the boot camp or outside the boot camp.
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:David Kovacs: Definitely coming from
a completely unrelated field was
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:pretty hard to, um, I guess find that
first opportunity in this, in this
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:new industry I'm trying to get in.
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:Avery: That makes a lot of sense.
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:I can't even really imagine, like,
how many vocabulary words that
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:architecture and landscape design
have in common with data analytics.
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:Like-
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:David Kovacs: Not many
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:. Avery: May- yeah, like, did you
guys, do you guys use Excel in, in
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:your industry at all or not really?
257
:David Kovacs: Uh, very little.
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:Yeah.
259
:N- in the last job I, no I think we
talk about it on, on the podcast every
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:so often, like if you opened Excel
like once a year for the past X amount
261
:of years, put that on your resume.
262
:That's probably where I was at.
263
:Okay.
264
:Yeah,
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:Avery: that's, that's some
years of experience, right?
266
:Uh, I love that.
267
:Um, okay, so let's talk about, yeah,
the hardest part was actually, you know,
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:transitioning out of your, your current
industry to a completely new industry and
269
:getting someone to take a chance on you.
270
:At what point did you start
applying for data jobs?
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:David Kovacs: I started applying
around the beginning of the year.
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:I got my resume together
and a portfolio together.
273
:Definitely wasn't perfect, but I
knew at the beginning of the year
274
:I just had to start doing it.
275
:Avery: Well, I think you joined
the accelerator like, like almost
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:mid-January or early January, and I
think you started this role in April.
277
:So like were you basically-
Yeah β¦ applying for jobs in January?
278
:David Kovacs: Yeah, I was applying
for jobs before I even started the
279
:accelerator, and I was applying-
I lo- β¦ the whole way through.
280
:Avery: I love that.
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:Okay.
282
:Um, and how many like applications
do you feel like that you sent before
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:you started landing interviews?
284
:David Kovacs: So I didn't do a very
good job at tracking that, but I had
285
:to have applied for well over 100,
maybe 200 jobs before landing my role.
286
:Avery: Okay.
287
:That's not bad.
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:Did you have like a lot of o- other
interviews, only a few other interviews?
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:David Kovacs: Only two other interviews.
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:Avery: Okay.
291
:That's still, that's still pretty good.
292
:Um, like a, an app- like if you've
applied for 200 jobs and you had like
293
:three interviews, I mean, that's not,
not terrible, especially, especially like
294
:coming from someone who doesn't have a
degree, who doesn't have prior experience.
295
:Like the, the usual, like an average
for, for data analysts right now
296
:is for every 100 applications you
send out, you get four interviews.
297
:So the job you ended up landing,
where did you find that job?
298
:Like what platform did you find it on?
299
:Do you remember applying for that job?
300
:David Kovacs: Uh, yeah,
found it on Indeed.
301
:Avery: Okay.
302
:On Indeed, and you applied for it.
303
:Um, and then do you remember, like,
how quickly they reached out to you
304
:and, and what that process was like?
305
:David Kovacs: So they reached
out to me pretty quickly.
306
:Avery: And then you had, like, a, a
phone interview with, like, a recruiter?
307
:Is that what it was?
308
:David Kovacs: Uh, I had a virtual
interview with my now supervisor and
309
:another person in the company where
we, you know, talked about the role and
310
:my experience, if it'd be a good fit.
311
:Avery: And, and this company that you're
interviewing with, I guess we should say
312
:what the company is and, and what they do.
313
:What- Yeah β¦ what does
your company do, actually?
314
:David Kovacs: So the company I work
for is called SmartPro Financial.
315
:We're Dave Ramsey SmartVestors,
if you've heard of Dave Ramsey.
316
:I've been listening to Dave Ramsey for
several years, so I was able to speak
317
:very enthusiastically in my interview
and my cover letter that I did.
318
:And the very first interview that I did,
my supervisor told me about how heβ¦
319
:I forget the exact number he gave me,
but it was well over 100 applicants
320
:that he reviewed, and he said I
was the only one who even mentioned
321
:Dave Ramsey in my cover letter, so.
322
:Avery: Very nice.
323
:Okay.
324
:So I'm, I'm hearing two things.
325
:One, you actually wrote, like, a
cover letter, like, as a PDF and, and
326
:just submitted it with your resume.
327
:Is that right?
328
:David Kovacs: Yeah, I
did the cover letter.
329
:I even found the CEO on LinkedIn
and wrote him a DM- Okay
330
:β¦ Avery: cold
331
:David Kovacs: message.
332
:Avery: Very cool.
333
:Very nice.
334
:So you did a, a cold message
and just a cover letter.
335
:And in your cover letter you mentioned
Dave Ramsey, which this company, you know,
336
:has, has lots to do with Dave Ramsey.
337
:And so that's probably one thing that made
you stand out, is you actually connected
338
:to the business on the business' level.
339
:You weren't just, like, another,
you know, data analyst applying.
340
:You were a data analyst who was, you know,
was familiar with and, and intrigued and
341
:interested in this Dave Ramsey world.
342
:So that kind of set you apart, you think.
343
:Is, is that what you're saying?
344
:David Kovacs: Yeah, and they,
they even do their own podcast
345
:and YouTube channel, and Iβ¦
346
:When I found out about them, I just
immediately started binging in, finding
347
:out about who they were and, you know,
what they stood for as a company.
348
:And at that point, I think, like, all
other options went out the window for me.
349
:It was, "I have to work for this company."
350
:So I sent my resume, sent a
cover letter, sent cold messages.
351
:I was even going to go show
up at their office with my
352
:resume if that's what it took.
353
:Like, I wanted to get in front
of somebody and talk to them,
354
:be like, "I wanna do this."
355
:Avery: Awesome.
356
:That goes to the whole, uh,
quality over quantity, right?
357
:And, like, you need to, you need to
apply to a lot of data jobs, but the
358
:ones you are really, really interested
in, the more effort you put into them,
359
:the higher chance you have of actually,
you know, moving forward with that.
360
:So that's really cool that
that, that paid off for you.
361
:Um, in the interview, did they
mention, like, uh, the bootcamp?
362
:Did they mention, you know,
being an architect previously?
363
:Did they mention your portfolio?
364
:You know, what did they
mention in the interview?
365
:Whatβ¦
366
:You know, obviously your interest in,
in the whole- their whole world was
367
:really impressive, but did they say
anything else about, like, why they
368
:w- were interested in you, David?
369
:David Kovacs: Yeah, they did question
about the bootcamp, about the internship.
370
:My supervisor did look at my
portfolio and questioned me about one
371
:particular project that I did in it.
372
:Avery: Super cool.
373
:Do you remember what project it was?
374
:I'm just curious, like, what
caught, what caught their eye.
375
:David Kovacs: So it was actually a random
Google Sheet project that I did that
376
:was completely unrelated to the program,
but that's primarily the program that
377
:we use at SmartPro is Google Sheets,
'cause we have a lot of people in our
378
:office and a lot of advisors outside of
our office that we need to collaborate
379
:with, so that's the tool that we use.
380
:Avery: Perfect, that makes sense.
381
:I love that.
382
:So you had a project off of the tool.
383
:I- I imagine that was listed
in the job description.
384
:So whenever you can have a project with a
tool they mention in the job description,
385
:that's great, and I think it's fantastic
that it was a project outside of the
386
:program because that's what I want, and
that's, like, the importance of, you know,
387
:the, the program in general is, like,
okay, you're gonna- I'm gonna show you the
388
:pattern of taking data and turning it into
a, a published project, you know, nine
389
:times in a row, and then you do that more
in the future, and you take what you've
390
:done in the past and you package them up.
391
:Like, that's part of the process
of just learning to do a portfolio.
392
:So I absolutely love that, and
I love that it's Google Sheets.
393
:Um, I'm a big fan.
394
:I like Google Sheets more than
Excel, but, um, Excel is just
395
:used- Yeah β¦ more, more often,
which is why we, we teach Excel.
396
:But they're basically the same,
so that's, that's perfect.
397
:Um, amazing.
398
:We talked about how we did a reference.
399
:Uh, I mentioned all the good work you did,
uh, in the, uh, on the internship project,
400
:and then you got, you got the offer.
401
:And then this is something, um, as
well that I think was useful to you.
402
:Um, you and I did some DMs back and
forth about the offer you got, and,
403
:like, what we thought maybe was a market
fair offer, and I think we were able
404
:to get you a, a little bit of a raise.
405
:Is that correct?
406
:David Kovacs: That's correct.
407
:Yeah, yeah.
408
:Avery: Love to hear it.
409
:Um-
410
:David Kovacs: Yeah, I told, me, I
told them an amount that I wanted,
411
:and we, we met, kind of met halfway
412
:Avery: Perfect.
413
:Yeah, that's, that's something
that I think a lot of
414
:negotiations kind of go that way.
415
:They say a number, you say a high number,
and we both compromise in the middle.
416
:But I think that's a win-win 'cause, you
know, we're making, we're making more
417
:that way and, um- Sure β¦ yeah, I think
that's what we talked about over, over DM.
418
:Um, okay, so now you have the job.
419
:I'm curious, like, what your job actually
looks like now on the day-to-day.
420
:Um, you mentioned you're
using Google Sheets a lot.
421
:Um, I guess what type of
problems are you doing?
422
:Are you interacting a lot with
internal people, with external people?
423
:What is the, the day in the life
look like for, of David now?
424
:David Kovacs: So I've been building a
lot of tools inside of Google Sheets to
425
:help us run reports more efficiently,
working with, um, the team I'm on.
426
:It's called OSJ, Office of Supervisory
Jurisdiction, where we're responsible
427
:for compliance and training.
428
:Mm.
429
:Avery: That sounds super cool.
430
:Um, so I love that- Well, I'm- β¦ you're
doing, like, the internal tools.
431
:That's always, like, a, a good role for,
for someone to have, is, like, they're
432
:the internal, uh, data tool person, and
you're making everyone's life easier.
433
:Uh, I think that's, that's really awesome.
434
:And the company and, like,
the team, how has that been?
435
:Like, have you enjoyed working with them?
436
:Do you feel like they, like, ever judge
you because you come from, you know, you
437
:don't come from a data background, you
don't come from a financial background.
438
:Uh, you come from, like,
this architecture background.
439
:Do you feel like that's ever
present in the company at all or no?
440
:David Kovacs: Uh, yeah,
so the culture's great.
441
:I've been getting along with everybody.
442
:Bosses, supervisors are very helpful,
as well as all the other employees.
443
:Uh, actually, a lot of us don't
come from a finance background.
444
:Um, and it was kind of explained to
me in the interview that they almost
445
:prefer that you do not come from a
financial background, because the
446
:way that we do things is very much
different than other financial firms.
447
:Avery: That's very cool to hear.
448
:So it's almost like your, your
inexperience or your untraditional
449
:background ended up being an
advantage for you, uh, in the end.
450
:Right.
451
:I'm curious if you could go back to,
you know, David as the architect,
452
:you know, like a year ago, unhappy,
looking to, to pivot, you know,
453
:deciding on data analytics.
454
:Um, like, what's something that you
would tell that David a year ago,
455
:the aspiring data analyst that he was
like, "Can I actually go from being
456
:an architect to, to data analyst?"
457
:What would you tell them?
458
:David Kovacs: I would say it's totally
possible, and don't wait to start
459
:Avery: I love it.
460
:Straightforward, straightforward,
and you can do it.
461
:That's, that's so glad
to, to hear it, yeah.
462
:Is there anything about your
career, your previous career,
463
:that you actually miss at all?
464
:David Kovacs: No, not really.
465
:I mean, um, I guess to speak to something
I said earlier about, like, being able
466
:to, like, go to the sites and see the,
uh, see the project that you work on come
467
:to life, look at this building, you know,
physical evidence of what you've done.
468
:But I feel like in data analytics
you have, like, real time evidence
469
:of the impact that you're making
with the tools that you're building,
470
:the reports that you're building.
471
:So I get just as good, if not
better, feeling from that.
472
:Avery: That's actually a
really interesting point
473
:because, yeah, I can't imagine.
474
:You work on something as an architect, and
then it takes like five years for you to
475
:actually, like, see it be, be finished.
476
:And s- and some
477
:David Kovacs: of these projects
are never even realized.
478
:Avery: So, so true.
479
:When I, when I was a chemical lab
technician, uh, I would, you know,
480
:set up these experiments and, you
know, monitor these experiments, and
481
:it would take like two hours for me
to see the results of the experiment.
482
:I remember thinking, "It sucks waiting
here to see if it actually worked or not,
483
:if, like, my work was, was valid or not."
484
:And that's something you get, like,
immediate feedback with a data analyst.
485
:It's like, does this tool work or not?
486
:Is someone using this tool or not?
487
:So-
488
:David Kovacs: Yes
489
:β¦ Avery: that is pretty satisfying.
490
:That is an interesting part of
data analytics I, I kind of forget
491
:about, I don't think I talk about.
492
:Um, what would you say to someone
who's, who's, like, thinking about
493
:maybe, maybe in the same boat as you?
494
:They're, they're listening to the
podcast in the car, they've been
495
:interested in the accelerator but
not sure if it's, if it's for them.
496
:You know, what, what advice would you give
them, or what would you say about that?
497
:David Kovacs: I'd say I
definitely got a lot of value
498
:out of the accelerator program.
499
:And again, like, what are you waiting for?
500
:Just hop into it, you know?
501
:Um, I think back all the time about,
you know, if I would've done this,
502
:like, several years ago, I could
already be so far into my career by now.
503
:And, you know, you don't wanna wait.
504
:Avery: It's, it's like they say,
like, the best time to plant a tree
505
:was 10 years ago, the next best
time is today or whatever, right?
506
:It's right now.
507
:Um, that makes a lot of sense.
508
:Um, in terms of, like, what's next
for your career, what are you,
509
:what are you focused on right now?
510
:Are you just, likeβ¦
511
:I mean, I know you're brand new,
so is it just, like- Hmm β¦ um,
512
:you're interested in, like, learning
from the people around you, you're
513
:learning and making an impact at this
company, and just excited about that?
514
:David Kovacs: Yeah, definitely lear-
you know, learning from the people
515
:around me, like you said, getting the
absolute best at my job that I can.
516
:And then from there, you know, I'd
like to learn more coding and get
517
:into more data engineering type stuff
maybe, like to learn how to, how I
518
:can help other departments in the
company, and I'd like to maybe even
519
:start doing some freelance work.
520
:Avery: That's awesome.
521
:The- you're just starting out in
your journey, and there's so many
522
:cool places, um, that you can go.
523
:It's, like, really that, that data analyst
role is such, like, a, a steppingstone
524
:role where you could literally go so many
different places, like you said, data
525
:engineering or- Mm-hmm β¦ or more coding.
526
:You know, those, all those different
routes that you have, and that's awesome.
527
:Well, great, David.
528
:I think, uh, everyone who's listened
to this episode will have, like,
529
:a really good feeling of, like, if
you're in a career that you hate, there
530
:is light at the end of the tunnel,
no matter how different it is from
531
:data analytics, and it can be done.
532
:You know, uh, it took you about a, a
year, I think, from maybe deciding to
533
:actually landing your data job-ish,
um, from joining the, the boot camp to
534
:landing your first data job, like 90
days, which I think is an obtainable
535
:timeframe for, for pretty much everyone.
536
:I think I'm grateful for you
for being willing to come on the
537
:show and be an example of what
that roadla- roadmap looks like.
538
:What does it actually look like to
go from, you know, architecture and
539
:landscape design to, to data analyst?
540
:Because as far as I know, I mean, I'm sure
you're not the only one on planet Earth.
541
:But you're the only one that I
personally know, and I've been
542
:doing this, uh, s- for six years.
543
:So, um, I think, I think you're, you're
a really great example, and I appreciate
544
:you coming on and sharing your story.
545
:I really appreciate it.
546
:David Kovacs: Thanks, Avery.