127: FASTEST Way to Become a Data Analyst (feels like cheating)....Career Hacking
Help us become the #1 Data Podcast by leaving a rating & review! We are 67 reviews away!
Breaking into data is hard. But it doesn't have to be if you CAREER HACK. Simply find someone's journey you can relate to, and reverse-engineer their steps.
💌 Join 10k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter
🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training
👩💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa
👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com//interviewsimulator
🔗 CONNECT WITH AVERY
🎵 TikTok
💻 Website
Mentioned in this episode:
🔮 Try DataFairy.io 100% free
Want an AI assistant to help you in your data journey? Try DataFairy.io for free to help you with Excel, SQL, Python, cold messages, networking, LinkedIn, and more!
Transcript
If you're trying to break into data analytics,
2
:you're probably overwhelmed with
advice, courses, and roadmaps.
3
:Maybe even including my own.
4
:But here's the truth.
5
:You don't need to
reinvent the wheel at all.
6
:Stop wasting your time trying to
figure it out all on your own.
7
:The right path for you to take is
actually sitting right in front of you.
8
:Hidden in plain sight.
9
:You just have to look hard at it.
10
:And here's what I mean by that.
11
:One of my favorite quotes ever is from
Brad Thor, who said, success leaves clues.
12
:And to me, that means you should be
able to look around you, find the
13
:people who are successful and figure
out how they became successful.
14
:If there's anyone or any amount
of success, There'll be some sort
15
:of trail or clues that you can
follow to recreate that success.
16
:With that in mind, I'd like to introduce
a concept I created called career hacking.
17
:It's where you find the people
who are already crushing it as
18
:data analysts, figure out exactly
what they did to get there, and
19
:then you follow their exact path.
20
:Why?
21
:Because success leaves clues.
22
:Step one is to identify those
who have already made it.
23
:Look for analysts who started where
you are now and are now working at top
24
:companies or have landed their dream role.
25
:And get specific here.
26
:I'm telling you, the more
specific you get, the better.
27
:Because if you're a pilot in the UK who
wants to break into data, Your journey
28
:will probably look a little bit different
than, say, a blue collar mechanic in
29
:the US trying to break into the field.
30
:Try to find someone who has
already done your exact journey.
31
:For instance, if you're a high school math
teacher in North Carolina looking to break
32
:into data, look for other math teachers in
North Carolina who have already done so.
33
:If you're a biology major in Florida,
then you should probably find
34
:other biology majors in Florida who
have already landed a data role.
35
:Then, break down their journey.
36
:Like I'm telling you,
really study it in detail.
37
:What skills did they learn?
38
:What projects did they showcase?
39
:What tools did they mask?
40
:What were they posting on LinkedIn?
41
:And what advice do they give
now to their former selves?
42
:Step two, reverse engineer.
43
:Reverse engineer their entire journey.
44
:I'm telling you, you don't have
to guess what works here, people.
45
:Just copy what's already proven.
46
:If someone used Tableau to get
noticed, then learn Tableau.
47
:If another person built an amazing
portfolio project that got them hired,
48
:Study the crap out of that project
and create your own version of it.
49
:I'm telling you, you don't have to create
your own data roadmap from scratch.
50
:Just steal the one that
works and is already proven.
51
:And if you're not sure where to
find all this information and
52
:how to copy it, it's available.
53
:I'm telling you, it's all over the place.
54
:It's just hidden in plain sight.
55
:You can study someone's LinkedIn
profile and learn a lot.
56
:You can see what their
profile picture looks like.
57
:What bullets do they have
in their experience section?
58
:What courses did they take?
59
:You can find that in
the education section.
60
:You can study their
portfolio or their GitHub.
61
:Because most of the time, the code
to recreate the project is right
62
:there, or there's some sort of
step by step instructions of how
63
:they actually built the project.
64
:It's all there for you for the take.
65
:Or if that's too hard, it's too much
work, then just do one thing and press
66
:the subscribe button to this podcast,
because I share a case study of a non
67
:technical person landing a data job
every single month on this channel.
68
:In these longer episodes, I
asked them exactly what they did.
69
:What they studied, where they worked
before, who they messaged, what type of
70
:portfolio they made, so on and so forth.
71
:And you can watch these episodes and
take notes to create your own roadmap.
72
:You guys, I'm seriously doing
all the hard work for you.
73
:All you need to do is press subscribe
because I've interviewed teachers.
74
:I've interviewed scientists,
engineers, people from India,
75
:people from Canada, people from
South America, people from Asia.
76
:Literally, anyone you could possibly
think of, I have interviewed them
77
:and learned how they transitioned
from what they did previously and how
78
:they landed their first day at a job.
79
:It's that easy.
80
:But remember, it's important to
stay consistent because it's not
81
:about just making a plan, but
you actually have to stick to it.
82
:Execution, day in, day out.
83
:It's boring, overcomplicating things.
84
:Find what has already worked
for others just like you and
85
:then apply it to your journey.
86
:That is career hacking and
it is your fastest route to
87
:success in data analytics.
88
:And let's make it easy.
89
:I have two case studies on the screen
and in the show notes down below
90
:that you can go study right now.
91
:So what are you waiting for?
92
:Let's do it.