Have you ever looked at a spreadsheet, those complex numbers, unearthly symbols, and was like, “Who even understands all this stuff?”
Well, someone does.
And they don’t just understand it, they know how to turn it into real business decisions, predictions, and even profits.
And that person is a data analyst.
Companies are constantly searching for the why behind their profits, sales, and other metrics, and data analysts are helping them do just this.
Today, data analysis is fast becoming one of the most in-demand digital skills career niche today.
But here’s the real question: How do you become a data analyst?
Is it just about learning how to use Excel or knowing how to code?
What is a data analyst’s job about?
And more importantly, how do you go from learning the skill to actually getting data analyst jobs, especially in today’s job competitive markets?
We know you’ve got the questions, and yeah, we’ve got the answers. In this blog, we’ll break it all down.
Let’s go.
What is a Data Analyst?
A data analyst collects data, studies it, and uses it to help businesses make better decisions that drive sales, conversions, and more profits.
Whether it’s sales numbers, user behavior, or customer feedback, they look at the patterns, break them down, and then tell the story behind the numbers.
According to a LinkedIn report made last year(2024), data analysis is one of the top 10 most in-demand skills globally, and it’s not even slowing down.
Today, several companies are more reliant than ever on data in shaping their future, making decisions, and analyzing performance, and this is the reason why the need for experts who know how to work with data is rising faster than ever.
So, if you’re wondering what a data analyst job is really about, or what data analysts do exactly, well, it’s more than just crunching numbers. It’s about asking the right questions, knowing where to look for answers, and being able to communicate those insights clearly to help businesses and team members act on them.
In other words, data analysts are like an intermediary between raw information and smart business moves, helping organizations understand their performance, the reasons, discover opportunities, and avoid risks.
And that’s what makes them so in demand and so valuable.
If you’re looking to switch careers or just start something new, then understanding what is the work of a data analyst is and what is data analyst is itself is the first step in knowing if it’s something you would even want to be interested in.
So, if you’re serious about learning how to become a data analyst, especially in a competitive job market, then you’re in the right place.
Because from here, we’re breaking it all down.
How to Become a Data Analyst
If you’ve ever felt the term data analyst sounds like a role meant for people who wear glasses, enjoy reading charts, and spend all day coding complex things, then you’re not alone.
However, that’s not the reality.
Becoming a data analyst doesn’t need to be complex; you don’t need to be a tech bro, you don’t need to have a computer science degree, and of course, you don’t need to be a math guru.
What you need are curiosity, a good eye for patterns and details, the desire to learn, and the ability to think logically.
Not more, not less.
In fact, if you’ve ever looked at your bank app and were like, “Where’s all my money going?” and then started breaking down your spending, then you’ve already had insight into what data analysts do.
Now let’s talk about how to become a data analyst for real, practically.
1. Know Why You’re Interested in It
Before jumping into tutorials, buying tools, or taking free courses, take a moment to pause and then ask yourself, “Why am I really interested in data analysis?”
Is it because you love solving problems?
Do you want a career that pays well?
Or are you simply trying to escape an unfulfilling job?
Knowing the reason you’re getting into data analysis will reveal if it’s the perfect niche for you or if you’re about to make a mistake.
And more importantly, it helps you stay focused, especially when learning gets hard or boring, because it will eventually.
2. Start With Data Thinking, Not Just Data Tools
You might be tempted to jump straight into SQL or Excel formulas.
However, being a good data analyst starts with thinking like one.
What does that mean?
You need to start learning how to spot patterns.
Getting used to asking questions like:
- Why is this number high?
- What changed last week?
- What could this trend mean?
This type of mindset is what differentiates a person who “knows Excel” from someone companies hire for thousands of dollars for data analyst jobs.
3. Learn the Tools
You can’t learn everything all at once. Start small.
- You can start with Excel or Google Sheets; they’re common, but very powerful, and most data analyst responsibilities start from here.
- Move to SQL – Now this is where it gets interesting, these are tools that help you talk to databases and pull information.
- After that, try Power BI or Tableau – these help you create the exact type of dashboards managers love.
You don’t need to be an expert on all of them before you start sending out applications for jobs.
Just make sure you know how to use them to solve simple problems.
4. Practice With What You Have Around You
If you can’t get real and actual data to work with? No problem.
Start from the small things.
For instance, you can start by analyzing your mobile data usage. Track your expenses. Study how long you spend on social media each day.
Create charts from it.
This way, you’re practicing with actual everyday data and not abstract.
5. Do Small Projects and Build a Portfolio
Once you’ve learned and understand the basics, start to apply them.
You can get free datasets on sites like Kaggle, Data.gov, or even scrape your own data from blogs or other e-commerce sites.
Afterwards, clean the data, analyze it, and turn your insights into visuals, maybe a report or dashboard.
Each eventually becomes a part of your data analyst portfolio, which is a very important thing, especially when you start applying for data analyst jobs in Nigeria or anywhere else.
6. Look for Internships, Volunteering, or Entry Roles
You don’t need a fancy job title to start working with data or a million-dollar data analyst job role with Amazon.
Check for willing organizations, it could be a small business or even a large one, then offer to help them organize their customer list.
You can even start by joining a tech community like and then volunteer to analyze event attendance.
Similarly, applying to internships, even unpaid ones, is to get hands-on practical experience.
It shows you’re not just learning for fun, it shows that you’re serious and ready to work.
Data Analysis Tools
If you’re intentional about landing data analyst jobs or even figuring out how to become a data analyst, especially today, where the job market has become more competitive than ever, you’ll need to have a good understanding of the tools to use and how to use them.
They aren’t just “nice to have tools.
They’re what will make your insights understandable, your reports readable, and your entire work as a data analyst faster, clearer, and more beneficial.
Let’s check out some of these tools and what they are:
1. Microsoft Excel
Microsoft Excel is where you start as a beginner data analyst.
And that’s because it’s simple, flexible, and powerful, and more importantly beginner beginner-friendly.
With it, you can sort, filter, and analyze raw data easily and quickly.
And while it might feel basic and non-technical, don’t underestimate how much it’s used in real workplaces.
In fact, many people still get hired into data analyst jobs just by being proficient in using Excel.
And when you eventually get to know how to use features like pivot tables, lookup functions, and conditional formatting, you’re already ready to start solving real business problems.
2. SQL (Structured Query Language)
As you go deeper and deeper, you’ll start to deal with databases, this is where proficiency in SQL becomes non-negotiable.
You’ll need SQL to pull data from large datasets, especially when you’re working on projects like sales records, user behavior logs, customer information, and many other types of data.
And yeah, since you’re asking what the work of a data analyst is, a great deal of it has to do with writing SQL queries that give business owners clear, usable answers from messy and complicated data.
3. Power BI
This helps to bring numbers to life.
Power BI is a Microsoft tool that enables you to create dashboards, charts, and other interactive reports from raw data.
Being proficient in it can really give you an edge, especially when dealing with companies where real-time visuals help managers track performance across plenty of departments.
So, if you’re applying for data analyst jobs in Nigeria or any other place, knowing how to use Power BI gives you a strong edge.
4. Google Sheets
Google Sheets is like Excel, but in the cloud.
It makes collaboration easy, especially if you’re on a remote team, working with clients.
Google Sheets enables multiple people to work on the same data file at once, it is perfect when you’re involved in group projects or other volunteer work.
5. Tableau
This is another important visualization tool, Tableau enables you to transform large amounts of complex data into beautiful and interactive charts and dashboards.
It is mostly used in bigger companies and international organizations, especially those with global data teams.
Tableau might indeed take you a longer time to master when compared to Power BI, however, many professionals say it’s worth learning if you’re aiming for data analyst jobs in data-driven sectors like finance, logistics, or even healthcare.
6. Python (for Data Analysis)
Once you’ve grasped the basics, Python can take your skills and your pay to a deeper level.
It helps you to automate repetitive tasks, clean huge datasets, and do more advanced statistical analysis that goes beyond just spreadsheets and dashboards.
Libraries like Pandas, Matplotlib, and Seaborn are popular tools inside Python that help analysts analyze data faster and better.
However, you don’t need to don’t need to start here, especially if you’re still figuring out how to become a data analyst with no experience,
But you absolutely need to explore it as you grow.
7. Google Data Studio (Now Looker Studio)
If you want a free tool you can use in building reports and dashboards online, then Google’s Data Studio is your friend.
It allows integration so seamlessly with Google Sheets, Ads, and other services, making it great for digital marketers, small businesses, and even freelance analysts who need to build reports that are not just attractive, but also shareable.
8. Jupyter Notebook
If you eventually decide to explore Python or R, then you’ll most likely be writing your code in Jupyter Notebook.
It allows you to mix text, visuals, and code all in a single place, and this is great for showing your thought process during an analysis.
It is especially useful for portfolio projects if you’re still learning or applying to data analyst jobs with no experience.
9. R (for Statistical Analysis)
R is actually very similar to Python; however, it is more focused on statistical modeling and projects that are more research-intensive.
It is widely used among academic researchers, economists, and analysts who deal with large survey data or financial models.
Truth is, you don’t have to learn R unless your work really demands it; however, if you’re in fields where statistical depth is key, R is still widely respected.
10. Canva
Yes, Canva
Now, this might come off as the odd one among the list, but when it comes to presenting your insights, especially in internships, freelancing, or startup roles, good design is very important.
Tools like Canva make it easier for you to create clean, readable visuals from your analysis when traditional dashboards don’t cut it.
It’s not necessarily a core data tool, but it helps you communicate with your work better.
Where and How to Get Data Analyst Jobs
Knowing the skills needed is one thing, but getting to land a data analyst job is a whole different story.
And it’s not surprising that this is the part where many people get stuck.
Landing a data analyst job isn’t as hard as it seems, only when you know how to position yourself well and where to look.
1. Start with Internships and Volunteer Roles
This might not be exactly what you are expecting, but it’s the most real and the most strategic way.
If you’re trying to figure out how to become a data analyst with no experience and land high-paying jobs, then start by looking for internships, NGO projects, or even small business gigs where they need help with their data.
Many organizations, even here in Nigeria, don’t have in-house analysts yet, and they’ll gladly work with someone who’s learning but can deliver solid results.
At Creaitz, we connect our community members with high-paying tech skills, with the inclusion of data analysis once there is a request for it from any of our partners.
This opportunity helps you to practice what you’ve been learning in real settings.
By taking on “unpaid” projects like that, you’re building your portfolio along the way, the experience is also giving you real-world expectations, and this often leads to referrals.
2. Use Freelance Platforms Strategically
There are several freelance sites like Upwork, Fiverr, and Toptal that you could use; they are not just for writers and designers.
There’s a growing market for data analyst jobs today, from building dashboards to analyzing data for small businesses.
You shouldn’t aim to go after the huge jobs since you’re just starting out.
Start with the smaller gigs, price fairly, and overdeliver, yeah, if you do well, many of those clients will keep coming back, and that way, you’ll bag a full-time contract.
3. Use LinkedIn as a Job Engine
LinkedIn isn’t just a place to upload your resume, comment congrats on every post, and then log out.
It’s where recruiters live, it’s where they search for people to hire, just like yourself.
The truth is, a lot of data analyst jobs in Nigeria don’t even get posted publicly; they’re filled through referrals or direct outreach via LinkedIn.
So, what do you need to do to make you stand out?
- Start by writing about what you’re learning (e.g., “I just created my first Power BI dashboard showing how sales increased in Lagos from Jan–April.”)
- Constantly post the things you’re working on, the achievements, and how you did it.
- Connect with hiring managers at data-driven companies.
- Use keywords like data analyst jobs in your headline or bio. This helps the LinkedIn algorithm notice.
According to LinkedIn’s own insights, “Candidates who post weekly about their field are 2.5x more likely to get a recruiter message.”
4. Target Startups and Growth Companies
If you’ve been thinking that the only places hiring analysts are banks and tech giants, then you’re wrong.
Because startups, most especially those in fintechs, edtechs, and even agrotechs in Nigeria, are hiring data analysts more than ever.
Many of these companies are moving really fast; they now constantly need to make data-driven decisions, and they do not always have massive teams.
So, they need people who can look at trends and say, “Hey, here’s what this means for our growth.”
You can search for these companies online.
Visit their websites. Check out their “Careers” pages.
If they’re growing fast, then that’s a sign that they probably need help with their data, even if they haven’t announced it yet.
5. Apply to Remote Roles Globally
Another good thing about data analyst jobs is that they are not limited to your city or even your country.
You can check out websites like:
They post available remote roles from startups and companies all over the world.
Many of these jobs aren’t even particular about having a degree.
They’re only interested in how well you can clean, analyze, and communicate data insights.
6. Stay in the Loop with Events and Communities
Many people land roles simply by showing up in the right communities.
And that’s very true, in fact, we wrote a story on how one of our community members landed a job role by being a part of our community.
Start by looking for tech meetups, virtual hackathons, data competitions, and Slack groups around data.
Follow companies like Creaitz, DataFest Africa, or TechCabal, they often post about open roles and events where you can connect with employers directly.
We had a similar type of event this month (SAS), and some of our members had secured job roles and earned valuable connections by attending the event.
You can access the recording here if you’ve missed it.
More importantly, don’t keep quiet. Sometimes, the best thing you can do is ask or make a simple post saying,
“I’m learning data analytics and looking to contribute to real projects. Is anyone open to working together?”
Even more than you think, this can open doors you didn’t know existed.
Data Analyst Jobs: How Much Does a Data Analyst Earn?
Just like the jobs in every other tech niche, the earning of data analysts varies depending on factors like location, scope of job, and level of experience.
Let’s check out a few reliable estimates:
According to Glassdoor, entry-level data analysts earn around $55,000 to $70,000 yearly.
With a significant years of experience, the salaries for data analyst job roles can rise to $1250,000 to $900,000 especially in sectors like tech, finance, and healthcare.
In Conclusion
Becoming a data analyst and getting a profitable job opportunity doesn’t have to feel complicated, overwhelming, or hindered by a lack of resources or the right knowledge.
Start small, stay curious, and keep learning.
And if you’re looking for a supportive space to grow, connect with others, and access free training, join us at the Creaitz community today.
We’re here to help you take the first step, and the next until your dreams become fully realized.
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