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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.