All language subtitles for 02_the-data-career-space.en

Compared with many other professions.

The data career space is relatively young.

This application of data driven work in
organizations has grown exponentially in

the last several decades, which means
there are many different opportunities and

much job security for you in the future.

Now that organizations have the technical
capacity to take on their own data

focused work.

They're looking for people like you with
the right skills to fill these jobs.

Traditionally, companies have filled
jobs in the data career space with

those from computer engineering
backgrounds or from statistics.

Increasingly there's been a shift
towards de-emphasizing engineering and

instead promoting analytical skills.

These skills can be learned in different
forums like the program that you're

currently enrolled in.

Let's look at a scenario, let's say that
an enthusiastic and enterprising person

that's you is starting a new position
at a company as a data professional.

Your company is a recognized
leader in its industry,

its workforce spans the globe and
you are its newest member.

It's your first day on the job and

you are ready to start working
during your orientation.

Your company grants you systems access and
onboarding documentation.

You're starting to have a clearer
picture of how information is generally

shared with employees.

You still have many questions about
the responsibilities of the position.

Later you watch a video from the quarterly
review meeting led by a company executive

watching the presentation

you get insight into the quarterly budget,
recent client interactions and

some general information
on an upcoming project.

You now have a broad
understanding of the company.

At this point, you still lack details
about your specific responsibilities.

During your first week, you're invited
to a virtual meeting of the data

professionals involved on the project
that you've been assigned to.

As each data professional outlines
their job responsibilities.

You take note of
the differences among them.

After each participant speaks, you begin
to realize that not all data tasks

are universal and that many data
professionals end up adapting

to meet the needs of the current
project and the needs of the data.

When you're new to a job,

I would discourage you from
over specializing immediately.

Instead taking on a variety of tasks
within a project is a great way for

newer data professionals to continue
developing their skill set.

As a member of a larger group of data
professionals, you're able to observe and

learn from your team members.

Once the analytical process is complete,

the results of the project
will need to be shared,

allowing everyone in the organization
to have access to the information.

This includes,
building user friendly interfaces and

communicating the findings
to different departments.

Working for a large company means that
there's a good chance that you will be

dealing with vast amounts of information.

This will require more work than a single
data professional can reasonably provide

because of this, you might encounter
scenarios where organizations have created

teams of data professionals. Throughout the
rest of this section, you'll take a closer

look at how complex organizations are
incorporating data professionals through

data teams and the division of
responsibilities within these teams.