Original subtitles

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.