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 attempted to tell and 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 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, and 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 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 will 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.