Earlier, I told you that
you already have analytical skills.
You just might not know it yet.
When learning new things, sometimes
people overlook their own skills,
but it's important you take
the time to acknowledge them,
especially since these skills are going to help you
as a data analyst.
In fact, you're probably more prepared than you think.
Don't believe me?
Well, let me prove it.
Let's start by defining
what I'm talking about here.
Analytical skills are qualities and characteristics
associated with solving problems using facts.
There are a lot of aspects to analytical skills,
but, we'll focus on five essential points.
They are curiosity, understanding context,
having technical mindset, data design, and data strategy.
Now, you may be thinking,
"I don't have these kinds of skills,"
or "I only have a couple of them."
But stay with me, and I bet you'll change your mind.
Let's start with curiosity.
Curiosity is all about wanting to learn something.
Curious people usually seek out
new challenges and experiences.
This leads to knowledge.
The very fact that you're here with me right now
demonstrates that you have curiosity.
That was an easy one.
Now think about understanding context.
Context is the condition in
which something exists or happens.
This can be a structure or an environment.
A simple way of understanding context
is by counting to 5.
One, two, three, four, five.
All of those numbers exist in
the context of one through five.
But what if a friend of yours
said to you, one,
two, four, five, three?
Well, the three will be out of context.
Simple, right? But it can be a little tricky.
There's a good chance that you might not even notice
the three being out of context
if you aren't paying close attention.
That's why listening and trying
to understand the full picture is critical.
In your own life, you put
things into context all the time.
For example, let's think about your grocery list.
If you group together items like flour, sugar,
and yeast, that's you adding context to your groceries.
This saves you time
when you're at the baking aisle at the grocery store.
Let's look at another example.
Have you ever shuffled a deck of
cards and noticed the joker?
If you're playing a game that doesn't include jokers,
identifying that card means
you understand it's out of context.
Remove it, and you're much
more likely to play a successful game.
Now we know you have both curiosity
and the ability to understand context.
Let's move on to the third skill, a technical mindset.
A technical mindset involves the ability to
break things down into smaller steps or pieces
and work with them in an orderly and logical way.
For instance, when paying your bills,
you probably already break down
the process into smaller steps.
Maybe you start by sorting them
by the date they're due.
Next, you might add them up and
compare that amount to the balance in your bank account.
This would help you see if you can pay your bills now,
or if you should wait until the next paycheck.
Finally, you'd pay them.
When you take something that seems like a single task,
like paying your bills,
and break it into smaller steps
with an orderly process,
that's using a technical mindset.
Now let's explore the fourth part
of an analytical skill set,
data design. Data design is how you organize information.
As a data analyst, design
typically has to do with an actual database.
But, again,
the same skills can easily be applied to everyday life.
For example, think about
the way you organize the contacts in your phone.
That's actually a type of data design.
Maybe you list them by first name instead of last,
or maybe you use email addresses instead of their names.
What you're really doing is designing a clear,
logical list that lets you call or
text a contact in a quick and simple way.
The last, but definitely not least,
the fifth and final element of
analytical skills is data strategy.
Data strategy is the management of the people,
processes, and tools used in data analysis.
Let's break that down.
You manage people by making sure they
know how to use the right data
to find solutions to the problem you're working on.
For processes, it's about making sure
the path to that solution is clear and accessible.
For tools, you make sure
the right technology is being used for the job.
Now, you may be doubting my ability
to give you an example from
real life that demonstrates data strategy.
But check this out. Imagine mowing a lawn.
Step 1 would be reading the owner's manual for the mower.
That's making sure the people involved, or you,
in this example, know how to use the data available.
The menu would instruct you to put on
protective eyewear and closed-toe shoes.
Then, it's on to step 2:
making the process, the path, clear and accessible.
This will involve you walking around the lawn,
picking up large sticks or
rocks that might get in your way.
Finally, for step 3,
you check the lawn mower, your tool,
to make sure it has enough gas and oil,
and is in working condition,
so the lawn can be mown safely.
There you have it. Now you know
the five essential skills of a data analyst.
Curiosity, understanding context,
having a technical mindset,
data design, and data strategy.
I told you that you are already an analytical thinker.
Now, you can start actively practicing these skills
as you move through the rest of this course.
Curious about what's next?
Move on to the next video.