How to Become a Data Analyst
by Danielle Antosz | Published on January 03, 2025
If you’ve ever wondered how companies figure out which marketing campaigns will succeed, how streaming services decide what shows to recommend, or how logistics firms optimize delivery routes, here's the secret: data analysts are behind the scenes, crunching the numbers.
In today's data-driven world, the role of data analyst has become increasingly important. Non-profits, governments, and businesses in nearly every industry use data analysts to translate numbers into actionable business insights.
Interested in joining this fast-growing industry? Let's look at what it takes to become a data analyst and why it's a career path worth considering.
What is a Data Analyst?
A data analyst collects, cleans, and interprets data to help organizations make better decisions. Think of them as translators, converting raw numbers into stories that businesses can act on. But don't worry—no actual translating is involved. Instead, it's about turning numbers and data into actionable insights and reports that business leaders can use to make strategic business decisions.
For example, say you work with customer complaint data. You might create a report explaining why most customers aren't satisfied with the quality of a specific product or what reasons customers give when they leave.
If you're a numbers-oriented, curious person, this might be the career for you. Companies use data analysts to drive efficiency and innovation—whether it's improving marketing campaigns, streamlining operations, or predicting customer needs. From healthcare to finance, data analysts are in demand across virtually every industry.
Simply put, organizations can’t afford to guess their path forward, and that’s where data analysts come to the rescue.
Key Responsibilities of a Data Analyst
The exact tasks you have will vary greatly depending on your industry and level. For example, a data analyst in a team lead role might spend some time managing and some time crunching numbers, while a newbie analyst might spend more time learning than analyzing.
In general, however, most data analysts will do some or most of the following:
Data Collection: Use tools and platforms to pull data from specific sources. Where the data comes from will depend on your industry and role.
Data Cleaning (aka Data Sanitation): To make the data usable, you'll need to clear it up. Hint: It’s a bit like spring cleaning but for spreadsheets. You'll remove duplicate entries, fix errors, and maybe discard outliers.
Statistical Analysis: Use tools like Python or R to identify trends, patterns, and relationships within the data.
Reporting and Visualization: Create charts, graphs, and dashboards using tools like Tableau or Power BI to make your findings easy to understand.
Collaborating: Work with business teams to define data-driven strategies.
Ensuring Data Accuracy: Keep an eagle eye on data quality and accuracy through validation and monitoring.
Day in the Life of a Data Analyst
As we've already discussed, your exact tasks will vary depending on your industry and role. However, other factors, like whether your team uses Scrum or the Agile project management framework, can also impact your day.
Here's a general idea of what your day might look like:
Start the morning with coffee (optional, but highly recommended) and check in with your team.
Pull fresh data from the company’s database using SQL.
Spend some time cleaning the data—removing duplicates, filling in gaps, or figuring out how to handle outliers that are skewing your data.
Run analyses in Python or Excel to answer questions like, “Why did sales spike last month?”
Create a visualization in Tableau to present your findings to the marketing team.
Collaborate with stakeholders to strategize based on your insights.
Wrap up the day by documenting your work…and maybe Googling “Why does my SQL query keep timing out?”
Technical Skills You'll Need as a Data Analyst
If you’re serious about becoming a data analyst, these skills are non-negotiable:
Excel: Mastering pivot tables and VLOOKUPs is just the beginning. You'll also need advanced skills like INDEX/MATCH and logical functions.
SQL: Essential for querying databases and extracting data.
Python or R: For statistical analysis and automating repetitive tasks.
Data Visualization Tools: Tableau, Power BI, or even Excel charts will help stakeholders understand what the data says.
Want to make sure you'll land a job at your top choice? Getting familiar with machine learning techniques or cloud platforms like AWS or Google Cloud can set you apart.
Industry Demand and Job Outlook
The demand for data analysts is growing rapidly, with strong job security due to the increased reliance on data across industries.
According to the Bureau of Labor and Statistics, opportunities for data analysts and data scientists are projected to grow significantly over the next decade, with a projected increase of 36% between 2023 and 2033.
Looking to get started in data analytics? Consider the CBT Nuggets course SQL for Data Practitioners Online Training.
Education and Training Resources
Most data analysts hold a bachelor's degree in fields like data analysis, computer science, statistics, mathematics, or economics. If you're still in college or looking to return, consider pursuing a specialized data analytics degree program.
However, many employers do not require a bachelor's degree. Certifications, online training courses, and job experience can boost your resume and show employers you’re serious about the field.
Here are a few popular certifications to consider:
Data Analyst Career Path and Progression
Most data analysts start as junior analysts, focusing on basic data manipulation and reporting under the guidance of senior data analysts or team leads. As you learn the ropes and hone your skills, you'll be able to move up the ladder and into roles like:
Senior Data Analyst
Data Scientist
Data Analytics Manager
Business Intelligence Director
Want to consider alternative career paths? Depending on your interests, you could also branch out into related roles like data scientist, business analyst, data engineer, or machine learning engineer.
What’s the Difference? Data Analyst vs. Data Scientist
Both of these roles work with data. In fact, the Bureau of Labor and Statistics only includes data scientists in its data sets. But there are some clear differences.
The key difference is a data analyst’s role is primarily exploratory (“What can this data tell us?”), while a data scientist’s role is experimental (“What can we use this data for in the future?”). Data analysts work to uncover trends and insights within existing datasets. Their work is rooted in presenting clear, actionable results—think dashboards, reports, and visualizations that businesses can use to guide specific decisions.
Data scientists, on the other hand, operate more at the frontier of data. They build predictive models to forecast future trends, design machine learning algorithms, and even find new ways to combine disparate datasets for deeper insights. While data analysts provide answers to today’s questions, data scientists often aim to answer tomorrow’s.
How Much Does a Data Analyst Make?
Now, let's talk about money! How much you can expect to earn will vary based on your experience level, location, and the industry you're in.
Like most industries, data analysts in larger cities can expect to earn more, while those in rural areas earn a bit less. Industries like tech, healthcare, and finance pay data analysts a bit more. Company size can also impact your salary range. In general, here's what you can expect to earn, from Glassdoor:
Experience Level | Average Salary |
Entry-Level (0-2 years) | $50,000 - $70,000 |
Mid-Level (3-5 years) | $70,000 - $90,000 |
Senior-Level (5+ years) | $90,000 - $120,000+ |
Conclusion
Data analytics can be a rewarding career choice for curious, detail-oriented people. With the right skills, education, and certifications, you can be well on your way to translating numbers into actionable business insights.
Whether you're just a data enthusiast, a recent grad, or looking for a career change, it's time to roll up your sleeves and dive into the data. Ready to get started? Enroll in a course or purse certifications to show potential employers you have what it takes.
Want to learn more about becoming a data analyst? Check out our complete list of training for data analysts.