Speaker:
00:00:00
If you're trying to break into data analytics,
2
:
00:00:02
you're probably overwhelmed with
advice, courses, and roadmaps.
3
:
00:00:07
Maybe even including my own.
4
:
00:00:09
But here's the truth.
5
:
00:00:11
You don't need to
reinvent the wheel at all.
6
:
00:00:13
Stop wasting your time trying to
figure it out all on your own.
7
:
00:00:17
The right path for you to take is
actually sitting right in front of you.
8
:
00:00:21
Hidden in plain sight.
9
:
00:00:22
You just have to look hard at it.
10
:
00:00:23
And here's what I mean by that.
11
:
00:00:25
One of my favorite quotes ever is from
Brad Thor, who said, success leaves clues.
12
:
00:00:31
And to me, that means you should be
able to look around you, find the
13
:
00:00:34
people who are successful and figure
out how they became successful.
14
:
00:00:39
If there's anyone or any amount
of success, There'll be some sort
15
:
00:00:42
of trail or clues that you can
follow to recreate that success.
16
:
00:00:46
With that in mind, I'd like to introduce
a concept I created called career hacking.
17
:
00:00:50
It's where you find the people
who are already crushing it as
18
:
00:00:53
data analysts, figure out exactly
what they did to get there, and
19
:
00:00:58
then you follow their exact path.
20
:
00:01:00
Why?
21
:
00:01:00
Because success leaves clues.
22
:
00:01:02
Step one is to identify those
who have already made it.
23
:
00:01:06
Look for analysts who started where
you are now and are now working at top
24
:
00:01:10
companies or have landed their dream role.
25
:
00:01:12
And get specific here.
26
:
00:01:13
I'm telling you, the more
specific you get, the better.
27
:
00:01:17
Because if you're a pilot in the UK who
wants to break into data, Your journey
28
:
00:01:21
will probably look a little bit different
than, say, a blue collar mechanic in
29
:
00:01:26
the US trying to break into the field.
30
:
00:01:28
Try to find someone who has
already done your exact journey.
31
:
00:01:31
For instance, if you're a high school math
teacher in North Carolina looking to break
32
:
00:01:35
into data, look for other math teachers in
North Carolina who have already done so.
33
:
00:01:40
If you're a biology major in Florida,
then you should probably find
34
:
00:01:44
other biology majors in Florida who
have already landed a data role.
35
:
00:01:48
Then, break down their journey.
36
:
00:01:50
Like I'm telling you,
really study it in detail.
37
:
00:01:53
What skills did they learn?
38
:
00:01:55
What projects did they showcase?
39
:
00:01:56
What tools did they mask?
40
:
00:01:58
What were they posting on LinkedIn?
41
:
00:01:59
And what advice do they give
now to their former selves?
42
:
00:02:02
Step two, reverse engineer.
43
:
00:02:04
Reverse engineer their entire journey.
44
:
00:02:06
I'm telling you, you don't have
to guess what works here, people.
45
:
00:02:09
Just copy what's already proven.
46
:
00:02:11
If someone used Tableau to get
noticed, then learn Tableau.
47
:
00:02:14
If another person built an amazing
portfolio project that got them hired,
48
:
00:02:18
Study the crap out of that project
and create your own version of it.
49
:
00:02:22
I'm telling you, you don't have to create
your own data roadmap from scratch.
50
:
00:02:26
Just steal the one that
works and is already proven.
51
:
00:02:29
And if you're not sure where to
find all this information and
52
:
00:02:31
how to copy it, it's available.
53
:
00:02:33
I'm telling you, it's all over the place.
54
:
00:02:35
It's just hidden in plain sight.
55
:
00:02:37
You can study someone's LinkedIn
profile and learn a lot.
56
:
00:02:40
You can see what their
profile picture looks like.
57
:
00:02:43
What bullets do they have
in their experience section?
58
:
00:02:45
What courses did they take?
59
:
00:02:46
You can find that in
the education section.
60
:
00:02:48
You can study their
portfolio or their GitHub.
61
:
00:02:51
Because most of the time, the code
to recreate the project is right
62
:
00:02:54
there, or there's some sort of
step by step instructions of how
63
:
00:02:58
they actually built the project.
64
:
00:02:59
It's all there for you for the take.
65
:
00:03:01
Or if that's too hard, it's too much
work, then just do one thing and press
66
:
00:03:05
the subscribe button to this podcast,
because I share a case study of a non
67
:
00:03:09
technical person landing a data job
every single month on this channel.
68
:
00:03:13
In these longer episodes, I
asked them exactly what they did.
69
:
00:03:17
What they studied, where they worked
before, who they messaged, what type of
70
:
00:03:20
portfolio they made, so on and so forth.
71
:
00:03:22
And you can watch these episodes and
take notes to create your own roadmap.
72
:
00:03:26
You guys, I'm seriously doing
all the hard work for you.
73
:
00:03:29
All you need to do is press subscribe
because I've interviewed teachers.
74
:
00:03:32
I've interviewed scientists,
engineers, people from India,
75
:
00:03:36
people from Canada, people from
South America, people from Asia.
76
:
00:03:39
Literally, anyone you could possibly
think of, I have interviewed them
77
:
00:03:42
and learned how they transitioned
from what they did previously and how
78
:
00:03:46
they landed their first day at a job.
79
:
00:03:48
It's that easy.
80
:
00:03:49
But remember, it's important to
stay consistent because it's not
81
:
00:03:52
about just making a plan, but
you actually have to stick to it.
82
:
00:03:56
Execution, day in, day out.
83
:
00:03:58
It's boring, overcomplicating things.
84
:
00:04:02
Find what has already worked
for others just like you and
85
:
00:04:05
then apply it to your journey.
86
:
00:04:07
That is career hacking and
it is your fastest route to
87
:
00:04:10
success in data analytics.
88
:
00:04:12
And let's make it easy.
89
:
00:04:13
I have two case studies on the screen
and in the show notes down below
90
:
00:04:17
that you can go study right now.
91
:
00:04:19
So what are you waiting for?
92
:
00:04:20
Let's do it.
