Data analysts are rapidly becoming one of the most in-demand and lucrative careers in the current economy and you might be wondering how to become a data analyst. As more businesses are being built and conducted online, data analysts provide them with invaluable information and business strategies through various data. As such, data analysts have become an essential asset for a company’s scalability and future success.

As a data analyst, you may be working with a wide range of organisations across a variety of sectors, providing insight and strategies from sources of data. Oftentimes, you will be dealing with unstructured data stored in different types of data management systems. Essentially, your goal is to take these scattered pieces of information and understand them. You’ll use your findings to further predict, or come up with ways to improve based on your desired results.

If this is a career that excites you, here is a simple guide that will help you get started on your first steps into the industry.


1. Gain theoretical knowledge and build a strong foundation.

Data analysis requires a large amount of technical knowledge and skills. One of the best ways to get started and give yourself a leg up is to get a fundamental understanding of the industry. As you research further and get a better overview of data analytics, it will help you decide if this is a career that you can see yourself building a future in while training yourself with the necessary skill sets required.

As the demand for data analysts has grown, the paradigm for the barrier of entry into the industry has shifted. During the early years, data analyst positions required you to have a Bachelor’s Degree. Even though many senior positions still do to this day, many entry level positions do not. Employers are looking for individuals who display the skill sets required and can perform the duties of the job. This means that you do not always need to go to university for four years to get an entry-level job anymore. You can build your skills through other means, such as self-study courses, certification programmes and vocational academies.

2. Train your technical skills.

As mentioned in the previous tip, you will be required to have a large amount of technical skills. Whether you are learning it through self-study or through formal training, there are some essential skills that you are required to have in order to be hired –– skills such as Python programming, SQL programming, statistical analysis techniques, data visualisation, project management and fundamentals of machine learning.

You should identify which of these skills you want to build first and focus your efforts into building solid fundamentals.

Aside from hard skills, you should also train your soft skills. Most employers are also looking for an individual with soft skills such as leadership abilities, communication and customer service skills, critical thinking and problem solving.

3. Do practices and mock analysis.

A great way to build up your data analysis skills is to gain some hands-on experience. The easiest and fastest way to start doing this is by joining a programme or diploma course that allows you to practice with real data sets, while providing you with 24/7 live tutor chat support to answer questions on Python, R, Tableau, and SQL.

Alternatively, you could collect open-source data sets to start your own projects. Pick a niche that you are interested in, come up with a hypothesis and collect the data that correlates to your project. With all the raw data in hand, you can start your analysis to prove or disprove your hypothesis.

4. Create a portfolio.

With all the practice analysis you will have done, it is ideal to collect your work in a portfolio. A portfolio is incredibly powerful and demonstrates your technical skills to potential employers. As your portfolio grows and becomes more refined, more potential employers will start to contact you for future opportunities.

If you are unsure of what to include in your portfolio, you could look at LinkedIn or popular freelance platforms to see how the experts in the field present their portfolios and get inspiration from them.

5. Consider taking a course.

Self-learning and independence are highly encouraged; however, there may be difficulties and roadblocks that you will encounter. It is a process of trial and error, and if you are looking to advance rapidly and learn the best approaches while minimising mistakes, you should consider enrolling on a Data Analyst Diploma programme with Pitman Training.

If you are looking to become a data analyst, Pitman Training provides you with top-quality education to help you on your career journey.

Unravel mysteries through data.

In a world driven by data and the insights that come from it, data analysts have become key members to any business or agency. If you’re looking to get started in the industry and have a drive to succeed, these steps can help you achieve your goals.