Hey, what's up, Gurus?
Welcome to section 2, Data Engineering Crash Course.
In this section, I'm going to be teaching you
the basics of data engineering.
And we're going to walk through some important concepts
that you're going to need to know for the DP-203.
Now, before we dive any further,
it's important that we have our You Are Here page
for the Introduction section.
So, you are here.
We are at the very beginning of a fairly long course.
So make sure that you have set aside
a timetable for yourself
so that you can kind of keep pace with where you should be
as you move towards taking this exam.
Also, make that you have set aside breaks for yourself.
Don't try and rush through the entire course with no breaks.
You're going to find yourself very frustrated,
even if that's just, "I'm going to watch 3 videos,
"then I'm going to step out,
"and I'm going to take a walk for 5 or 10 minutes,
"and then I'm going to sit back down to it."
Just make sure that you are pacing yourself for this exam.
Now, like any good Introduction section,
we are going to be building the foundation.
And your building
is only going to be as good as its foundation.
So we're going to start that process here by diving in.
We're also going to talk about core concepts.
What is data, exactly? What's data engineering?
How do those 2 play together?
Lastly, a few key points for you to keep in mind.
First, think buckets.
So as we go through the various tasks for this exam,
I want you to think about what services
those tasks could be performed in.
Is it Data Factory, Databricks, Azure Stream Analytics,
Synapse, or multiple services?
I want you to think about the buckets
as we go through these tasks,
because it's really going to help you in the exam
and also in your career to be able to think about
where those things would live.
Next, repetition.
Key services and key concepts will be repeated.
So the first part to that, if you are not getting something,
go all the way through the section,
don't get hung up at the very beginning.
It may be something that we cover multiple times.
And the other side of that repetition,
we have hands-on labs.
And as you go through the sections
you will see hands-on labs
reinforcing some of important concepts from each section.
So if you're not getting something clearly
all the way through, do the lab as well.
At the end of that, you might go, "Oh, I get it now."
If you haven't,
please go back, watch it again, ask questions.
We're here to help, and we will make sure
that you get where you need to be.
Finally--yes--you need this for your career, too.
For most data engineering positions
it's more than a certification.
There are very few data engineering jobs
that don't require some sort of onboarding exam, right?
Entrance exam, or whatever you want to call it.
You're going to need to know the basics of data engineering.
You're going to need to know
beyond the basics of data engineering
to be able to be a competent data engineer.
So just getting the certification is not enough.
And while I wouldn't recommend
that you run off into the weeds
in other concepts that don't relate to the 203,
what I would suggest is you leave some notes for yourself
of things that you would like to go back
and learn more on as the course progresses.
That way you won't get lost, and off in the weeds,
and miss your deadlines for completing the 203.
But you'll have some good notes
for where you should go from here.
All right, I hope that has been helpful.
Let's dive into this section.