Data & Analytics Blog


How To Build A Career In Data Analytics

Posted by LPA Software Solutions on Aug 20, 2020 11:01:00 AM

Demand for data analysts has boomed around the globe. Experts predict this trend is going to continue. Data scientists, analysts, and engineers will all be needed in the years to come.

If you’re thinking about starting a new career path, then it might be time to look at this growing field. How can you build a career in data analytics though? This step-by-step guide will help you get started on this journey.

Education for Data Analytics Professionals

The first step on most career paths is education and training. This is true for anyone looking to have a career in data.

Most data analysts start with a bachelor’s degree in a related field, such as computer science. From there, they’ll branch out into more specific training for the role they want.

Some training and skills are common to almost all data professionals. You’ll probably want to learn programming in both R and Python, for example. While learning one or the other is useful, knowing both will make you more versatile.

What else should data analysts master? Statistics and mathematics are fundamental. You’ll need to correctly interpret data, and courses in these areas should provide the necessary skills.

SQL, web development, and data mapping are also important.

Achieving Certification

You can take individual courses and build some of these skills separately. A better plan of action might be to seek out specific data analytics certification.

Most certificates will require you to have mastered some skills already. Some provide well-rounded training, while others will focus on a specific area.

Choosing a certification should reflect both the skills you want to learn, as well as the role you’re seeking.

Keep in mind that new tools and languages are always being developed. That means new skills are always emerging. A few years ago, machine learning was hardly on anyone’s radar.

Choose a Role

If you want to build a career in data, you should have some ideas about the career paths available. This means taking a look at the different roles available.

Some of the most common careers in data include:

  • Data Analyst
  • Database Administrator
  • Data Engineer
  • Machine Learning Engineer
  • Data Architect
  • Data Scientist

The differences between these roles may not be clear at first. A data architecture, though, has different responsibilities than data engineers. The architect creates blueprints for data management systems.

Data engineers build those systems. The data scientists then use the systems to run their algorithms.

If building and maintaining the data management system doesn’t excite you, then data engineering may not be the right kind of position for you.

Don’t Forget Soft Skills

If you’re interested in data analytics as a career path, then you might focus on the hard skills you need. You shouldn’t forget the soft skills.

Soft skills can be just as important as programming or SQL skills. They include skills like communication, problem-solving, and analytical thinking.

Soft skills will serve you well in almost any career, which is another good reason to work on them. Learning them can be a bit more difficult. There often aren’t courses dedicated to learning analytical thinking, unlike programming classes.

Still, seek out opportunities to practice your soft skills. You’ll be better equipped for a career in data analytics as a result.

Find Networking Opportunities

Once you have the right training and accreditation, it’s time to find job opportunities. Networking can be one of the best ways to find those opportunities.

Networking is also important when you want to advance your career. Knowing the right people can help you land a higher position at another company or even help you move up the ladder.

You should network as much as you can. Conferences, workshops, and seminars are great opportunities. Peer support networks are also great places to meet others in the field.

Continuing Education for a Career in Data Analytics

Ongoing education is part of building a successful career in data analytics. If there were courses you couldn’t take the first time around, you can always take them later.

You may also need to learn new tools and technologies as they’re developed. A new programming language may eventually replace Python. SQL may eventually be replaced by something else.

Machine learning is evolving fast, and so are the tools to manage it. Best practices around constructing databases are always changing too.

The best thing you can do is stay up to date. Take courses when necessary, and learn new skills whenever possible. You can also look at industry reports and more.

If you want to advance in your career, then focusing on leadership and management skills can also be important. You may want to take courses dedicated to these areas.

What’s Driving Demand?

Before you settle on a career in data, you probably want to know the outlook for jobs in this area. Right now, the outlook is quite good.

Why? More business leaders understand that data is the key to competing effectively. Data has become more valuable than gold.

What’s more, is that businesses will be generating more of it in the near future. Already, many businesses have trouble keeping up with the amount of data they collect and generate.

As more devices come online in the Internet of Things, data creation is going to increase. The growth of machine learning is also driving the need for more data.

More data means a need for more people to work with it. It drives a need for better structures and algorithms, as well as more skilled analysts.

In short, demand for data analysts and other professionals seems poised to keep growing. If you’re looking for a job that will have plenty of opportunity in coming years, this could be the one for you.

The Analysis of a Smart Career Move

A career in data analytics could be the right move for you. As demand continues to increase, and new technologies appear, the need for talent is only going to grow.

Wondering where your data analytics career could go next? Get in touch with us to discover training and much more.

Topics: Training, Data Science & AI