Hello everyone, and welcome!
It’s time for another 365 Data Science special, and this time we’ll talk about an alternative
way of getting into data science.
That’s right – we’ll talk about becoming a data analyst.
More specifically, we’ll look at who the data analyst is, what do they do, how they
fare in terms of salaries, and what skills and academic background you need to become
one.
But before we get started, we just want to remind you that there are several attention-worthy
career opportunities you can explore within the field of data science itself – and those
are: • data analyst;
• BI analyst; • data engineer;
• data architect; • and, of course, data scientist.
We’ll do a video just like this for each of the other career opportunities, so be sure
to check them out too!
Alright!
So, the data analyst.
Who is the data analyst exactly?
Data analysts are the real troopers of data science.
They’re the ones who are involved in gathering data, structuring databases, creating and
running models, and preparing advanced types of analyses to explain the patterns in the
data that have already emerged.
A data analyst also overlooks the basic part of predictive analytics.
That’s the “elevator pitch of the data analyst”.
But to really get an idea of what it means to be part of a team like that, we need to
look at what a data analyst does.
As it turns out, quite a lot.
A data analyst is both a thinker and a doer who doesn’t hesitate to roll up their sleeves
and dig into the numbers.
Data analysts extract and analyze data with a “can do” approach and then present data-driven
insights to underpin decision making.
They also develop and build analytics models and approaches as the basis for a company’s
strategy and vision.
On top of that, they are often responsible for identifying and extracting key business
performance, risk and compliance data, and converting it into easy-to-digest formats.
So, as you can see, agility to shift between strategic projects and operational activities
a must.
If you think that sounds a bit lonely…
Think again!
Data analysts are great team players and work closely with various departments and leaders
within the organization.
That’s super important if they want to be effective in this role.
So, the ability to communicate well and influence is critical here.
So what does all this mean in terms of salary?
How much does a data analyst earn?
Glassdoor and PayScale were kind enough to share their insights.
If you’re taking the first steps in your data analyst career, you can expect an average
pay of $57,000.
As you reach 4-6 years of experience, your compensation will also go higher ($68,000
median annual salary and an average bonus of $4,705).
You’re based in the UK?
The average compensation for data analysts with less than 1 year of experience (including
bonuses and overtime pay) is £23,870.
In terms of data analyst job growth, if you already have 1-4 years of experience as a
data analyst, you can expect annual earnings of £25,853.
That said, let’s address the elephant in the room and talk about how to become a data
analyst.
Are you now considering a career as a data analyst?
As we already mentioned, that’s certainly a great option to explore, both on its own
and as a gateway into data science.
However, there are a several points you should consider before you can determine with confidence
whether a career in data analytics is the best career path for you.
First on this list – Education.
What education do you need to become a data analyst?
Well, a Bachelor’s degree in IT, computer science or statistics will give you a strong
advantage.
However, equivalent experience in data and business analytics also fit the bill.
The good news is, even if you lack the background and the experience, you still have a good
chance of getting a job as a data analyst.
There are various ways to learn, such as taking qualification trainings or completing an online
course or two that’ll give you the foundation you need to match your teammates’.
Both paths should increase your chances to land an internship at a high-profile company
and build your career from the ground up.
Some of you might be thinking right about now that an entry-level position just doesn’t
have a glamorous enough ring to it, and it isn’t how you imagined launching a successful
career as a data analyst.
But this just may be the best way to achieve your goal.
In most companies, you’ll be able to gain valuable experience and take advantage of
many in-house training opportunities.
Ultimately, pile up enough qualifications and skills, and you will become a highly competitive
work candidate.
Speaking of qualifications and skills, what data analyst qualifications you should acquire
to begin with?
Well, as a data analyst, you’ll have plenty of tasks to juggle on daily bases.
That means you’ll need a variety of skills, including technical, practical, and soft.
We’ll review them here, but if you want to see the definitive list, we’ve put a
link in the description to a massively helpful article about starting on the data science
career path.
Alright – technical skills.
Obviously, you’ll need some programming background in Python, R, or the likes.
You’ll also need to have some expertise in SQL and a good understanding of how relational
database management systems work.
In that sense, it would be optimal if you know how to extract and analyze data from
diverse resources (meaning multiple data marts and file formats).
Knowledge of Tableau and how to work with large data sets is also a very big plus.
Have you heard of Microsoft Excel?
You won’t make it in the field of data analysis if you haven’t.
Make sure to familiarize yourself with some of the more advanced analytics and formulas
before you go into your next job interview.
Finally, even though some things are learned on the job, a good grasp of statistics and
an ability to work with some of the best statistical software packages is almost a prerequisite
here.
But know your way around quantitative methods, confidence intervals, sampling and test/control
cells, and predictive modeling, and you’re well on your way to the realm of data analysts.
What about practical skills then?
Given everything we’ve discussed so far, it shouldn’t come as a surprise that there’s
a decent chunk of those too.
For example: • Strong attention to detail and ability
to quality check your own work to ensure data mistakes are caught prior to work delivery;
• Advanced analytical and data interpretation skills;
• Hands-on, problem-solving skills and a proactive approach to problem resolution in
general; • The ability to initiate and drive projects
to completion with minimal guidance; • Confidence to challenge thinking and offer
opinions, thoughts, and insight; • The ability to communicate the results
of analyses in a clear and effective manner; • And of course, quick learning skills!
In terms of soft skills, it’s a pretty standard package --
• You’ll need your excellent communication skills – both verbal and written;
• An ability to articulate complex concepts in a clear and concise manner;
• Some level of flexibility so you can collaborate effectively in any work environment;
• And…
Good listening skills!
Alright!
Now you’re aware of the most important aspects of the data analyst job and what skills to
focus on in order to become one.
Nevertheless, if you feel like you still need additional career advice and a more detailed
analysis of the career opportunities in data science – we wrote a very long article about
this, and the link is in the description, if you want to learn more.
In the meantime, thanks for watching and good luck on your data science journey!