‘If you study X course, you can work anywhere’ is a familiar phrase in Nigeria. Students hear it in their final years of secondary school, on career day, right before filling a JAMB slip. Sometimes it comes as consolation from a tired lecturer who knows that at least half the class would rather study a different course. After graduation, many students realise that this statement is more theoretical than practical.

Data analysis is one of the few exceptions. It remains one of Tech Twitter’s most popular and in-demand fields. From NGOs to telecommunications and even healthcare, data analysts are needed everywhere.  

With such a high-value skill, it’s only natural to want to get in on the action, but where do you start? 

In a recent conversation with Zikoko, expert data professionals Tina Okonkwo and Odun Aliyu share honest insights into data analysis as a career, the mistakes they made early in their careers, and seven things every beginner should know.

1. It’s Not As Hard As It Sounds

A lot of people think about data analytics and imagine sweating in front of a computer while looking at complex numbers. But half of a data analyst’s job is decision-making. Every person is a living database, and there is an infinite amount of data flying around. According to Odun, not using data to make informed decisions is the same thing as having money in your bank account and choosing to starve. To put it simply, a data analyst’s job is to use data to provide solutions to business problems. As long as there are people who need to make decisions without doing guesswork, there will always be a need to analyse data. 

2. Learn How to Use Excel Before Attempting to Code

Both experts admitted to making the same mistake early in their careers.  Before pivoting into data analysis, Odun had been told that it was best to learn the hard skills first. So, she decided to learn Python, a programming language. When the class instructor began to teach back-end programming, Odun realised that she had spent too much time learning the wrong skill.

According to her, a data analyst’s primary job isn’t to write complex formulas; it is to solve problems. Any skill you want to learn should be a tool that directly connects you to your problem-solving goal. She recommends starting by learning how to use Excel before moving to SQL, Visualisation tools like PowerBI and finally, programming languages or Cloud knowledge.

3. Online Courses Won’t Always Work

The fact that everyone is taking an online course does not mean that it is the best way to learn. Each person’s learning pace is different.  Some people would rather be in tech academies, while others would rather watch videos or have someone teach them.  Some prefer being self-taught. Any beginner can find free tools on Coursera, Udemy, YouTube, DataCamp, and Microsoft Learning

4. Make Your Progress Visible

Most of a data analyst’s work happens behind the scenes. Because of this, no one is going to know what you’re doing if you’re not vocal about it. Using herself as an example, Tina mentioned that she started data analysis by watching YouTube videos on her phone. Since she had no laptop, she borrowed one to practice every night. Regardless, she was consistent with posting her achievements and learning projects on her Twitter page. When a project she built went viral, Tina received three offers for a laptop. What we’re saying is, you need visibility to get the assistance and opportunities necessary for growth.

5. You Need People Just As Much As You Need Numbers

‘Communication is key’ is a cliché phrase for a reason. Unlike many tech fields, data analysts can’t hide behind computers and let their work speak for them. People pay you because they don’t understand the graphs on the screen. It’s your job to tell them what it means and the solutions they represent. You also need business understanding because to solve a problem, you first have to find it. To do that, you need to be able to ask the right questions. 

Storytelling is another underrated skill in data analysis. Using data to tell a story transforms it from a set of numbers into a real solution. While practising or building a dashboard, think about the audience you’re building for and the solution they need from you. That way, it is easier to present your findings. Soft skills are just as important as technical skills. 

6. Stop Collecting Certificates

 Yes, Certifications are important to build credibility, but no one is hiring certificates. Instead, employers will hire you based on what you can do. Chasing certificates also encourages overlearning. Learning every skill you can find makes you a Jack of all trades and a master of none. It’s important to build on a particular skill before moving to the next. Working on as many projects as you can and practising helps you build skills faster than just collecting certificates. After learning, stop waiting until you feel ready before you apply for jobs. According to Tina, as long as you understand 70% of a job requirement, you’re good enough to do the job.

7. Your Social Media is Your CV

When you start building projects, reach out to your friends, church members and businesses around you to ask for datasets. Potential employers need to see that you are providing solutions to real problems. You can also base your projects on trending world issues. Doing that makes it easier to catch the attention of potential clients.

Another important tip for growth is to join a community. A lot of job vacancies in the data community are filled through recommendations and referrals. Attending events, meet-ups, and building relationships will give you access to the right set of people. 

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