All language subtitles for 02_the-top-skills-needed-for-a-data-career.en

All data professionals
share a love of

data and a desire
to solve problems.

While wearing their
analytics hat,

data professionals lay out

the story that they're
tempted to tell.

Then they poke it
from several angles

with follow-up investigations to

see if it holds water

before bringing it to
their decision-makers.

In doing so, they rely
on their programming and

investigative skills to guide

others towards
informed decisions.

Data professionals also combine

a knowledge about how
to do practical tasks

with an awareness of what makes

communication and
collaboration successful.

Later, we'll dig deeper into

the elements of
communication and discuss

the ways communication enhances

and structures your work
as a data professional.

For now, let's examine
some skills and

attributes that are

applicable across
data-driven careers.

Working in data
analytics requires

a mix of business sense and
knowledge in gathering,

manipulating, and
analyzing data.

Our goal is to prepare
you to develop

the competencies
needed to succeed.

Let's start by discussing
some interpersonal skills.

Often, these are referred
to as people's skills.

They focus on communicating
and building relationships.

Interpersonal skills
are critical.

In this field,
there's a high degree

of interaction
between stakeholders.

This is especially
relevant now with

team members often working

collaboratively
across the globe.

Very often, work
conversations are

the starting point and the
fuel that drives projects.

Because of the cyclical
processes within data analysis,

communication is always ongoing.

Another important skill
is active listening.

This means allowing
team members,

bosses, and other
collaborative stakeholders,

to share their own points
of view before offering

responses so that

each exchange improves
mutual understanding.

You can actually practice
active listening.

Next time you speak
with someone,

put extra effort into
listening beyond their words.

Focus on what they're
trying to communicate.

Your listening and
communication skills

will play a huge role in

helping you capture

effective insights and
informed decisions.

We'll take a closer look at

communication a little
later in this course.

There are other things
you'll need to consider.

As a data professional,

you'll search for information

hidden within a large amounts

of data by applying
critical thinking skills.

Along the way, you'll
investigate the connections

between a variety of
different data sources,

as you search for
trends and indicators.

Think of yourself as
a data detective.

Project data can
come directly from

your organization or
from other sources.

You might be lucky and receive

a well-formatted
spreadsheet or database,

but quite often,
you will need to

prepare the data to get started.

This process is known
as data cleaning.

This is where the data is
reorganized and reformatted.

The goal is to
remove anything that

could create an error
during analysis.

This process includes

tagging and consolidating
duplicates,

irrelevant entries, structural
errors, and empty space.

Once you have everything
in the proper format,

you can then filter
out unwanted material.

Now, your data is
ready to be analyzed.

It's time to look for
trends and tendencies.

Often it's very helpful to
render the data visually to

reveal additional
insights through

charts, dashboards and reports.

Graphic tools be very useful
in identifying patterns,

as well as in sharing
information with others.

You will explore this in
greater detail later and have

opportunities to practice
compiling visualizations too.

You'll also learn about
more advanced skills

like building models and
machine learning algorithms.

These tools will help you and

other data professionals
assess information accuracy,

analyze specific data segments,

and predict future
business outcomes.

Your hard work will assist

leaders and other
decision-makers in your company,

providing them access
to a rich variety of

perspectives on different
sets of information.

With demand for data
analytics increasing

across all types of
companies and businesses,

you will likely find
opportunities in

an industry that you are
personally interested in.

Next, we'll take a look at
working in the data field.