In the age of big data, being able to analyze information is not just a useful skill — it’s a career superpower. Businesses around the world depend on data analysts to help guide their decision making, to spot trends and to solve real-world business problems. Whether you’re coming from the ground-up or you have technical experience and want to make the switch, here’s a step-by-step path for you to learn data analysis from scratch in 2025.
By the time you’ve worked through this piece, not only should you have a clear idea of what it takes to become a data analyst, but you should also have a plan in place to select the right data analyst course (or set of data analytics courses) that meet your career goals.
In finance, healthcare, marketing, e-commerce, tech and many other industries, data is driving strategic decisions, and the need for data analysts has never been greater. In reality, data analysis is still cited as one of the most sought-after skills worldwide according to LinkedIn.
Here’s why learning data analysis in 2025 makes sense:
Information is everywhere: From your Fitbit to your favorite streaming service, information is being collected and analyzed.
Portability of skill set: Data analysis is an in-demand skill across many industries (not just tech).
Good earning potential: Entry-level data analysts can make more than $70,000 per year, while more seasoned pros can climb into the six figures, according to Glassdoor.
Career mobility: There are many data analysts who move on to become data scientists, business analysts, product managers, consultants and more.
This learning path is for someone who wants to learn the tools required to be a data analyst. It will also be a logical process for beginners and anyone who wants to become a data analyst, even if you are a student, graduate, employee or anyone looking for a career change. Let’s break it down:
Step 1: What Is a Data Analyst?
Before exploring tools and courses, learn what data analysts actually do.
Key Responsibilities:
● Aggregate, clean data from various sources
● Review data to identify trends and insights
● Build dashboards, and reports in Excel, Tableau and/or Power BI
● Share results with stakeholders to shape direction
Having a solid grasp of this will help you gain insight into each learning curve and choose the right data analyst course that teaches the right job-content skills.
Step 2: Get a Fundamentals in Statistics and Mathematics
The basis of everything is data analysis with a background in statistics. Ken fucking zealous about probability, distributions, hypothesis tests, regression analysis is important.
Topics to Cover:
● Mean, median, mode
● Standard deviation and Variance
● Correlation and causation
● That was a linear and time series analysis.
You don’t need to be a math whiz — concentrate on applicable things that relate to data.
Step 3: Become a Microsoft Excel or Google Sheets Wizard
Excel is still very much a popular tool for data analysis, at least in positions that deal with business and operations data.
What to Learn:
● Functionality such as VLOOKUP, INDEX-MATCH, and pivot tables
● Data cleaning techniques
● Conditional Formatting and Simple Dashboards
You will often find most introductory data analytics courses starting with Excel - it's easy to grasp and very popular.
Step 4: Study a Programming Language (Python or R)
Programs can help automate tasks and do more sophisticated statistical analyses. Python is now one of the most popular choices for data analysts because of its readability and large ecosystem.
Skills to Develop in Python:
● Data wrangling with pandas
● Visualizing data in matplotlib and seaborn
● Working with APIs and JSON
● Scripting to cleanse and process data
Those enrolled in a data analyst course expect to see: Demonstrations of practical hands-on coding exercises and references to real datasets which they can practice with.
Step 5: Master SQL to Query Databases
The vast majority of the world’s data exists in databases. This is where SQL (Structured Query Language) plays a key role in accessing and processing this data effectively.
What You Should Know:
● SELECT, JOIN, GROUP BY and WHERE statements
● Subqueries and nested queries
● Aggregation functions
● Fundamentals of cloud indexing and performance
A great number of employers state that SQL skills are a must-have in almost any data analyst's job description.
Step 6: Test Data Visualization Tools
Data storytelling is the difference between being a good analyst and a great one. - Visualization tools help deliver insight in a clear and compelling way.
Popular Tools:
● Tableau
● Microsoft Power BI
● Google Data Studio
● Libraries -plotly, dash etc in Python protocols.
Select a data analytics course that has hands-on projects where you’ll get to build dashboards and data stories.
Step 7: Engage in Real Work Projects
Once you have some basic tool skills, it’s time to handle the animals themselves. Projects reinforce what you learn and are part of your portfolio.
Project Ideas:
Track COVID-19 and compare the data with more than 40 indicators of socioeconomic and demographic factors.
Do sales forecasting of its retail store
See you money, visualize financial trendlines
Create a model that segments the customer base of an online retailer based on purchases.
Platforms such as Kaggle, GitHub and personal blogs are some of excellent platforms to display your work.
Step 8: Create a Portfolio and Resume
A portfolio is a way to demonstrate what you are capable of doing to prospective employers. List 3–5 unique projects that demonstrate varying tools and techniques.
Pro Tips:
Use GitHub to store code and notebooks
Illustrate your LinkedIn profile or personal website
Write mini-case studies that outline your process and discoveries
When choosing a data analyst course, look for ones that help you where portfolios are concerned.
Step 9: Obtain Certifications (If Desired but Not Necessary)
Certifications aren’t required but they can help build your credibility — especially in the case of a career transition or if you don’t have any previous background in restaurant management.
Top Certification Options:
Google Data Analytics Certificate: You can’t turn around these days without hearing someone talk about all things data.
IBM Data Analyst Professional Certificate affected by past or future actions of other particles.
Microsoft Certified: Data Analyst Associate
Courses from the best colleges on Coursera, edX, and Udemy
All of these programs are organised into well-structured data analytics courses with mentorship, quizzes, and capstone projects.
10 – Consider Applying For Jobs or Internships
With your skills honed and portfolio polished it’s time to start applying for roles such as:
● Junior Data Analyst
● Business Analyst
● Research Analyst
● Reporting Analyst
Tailor your résumé to the job and use your cover letter to explain how your data skills match the company’s mission.
So with hundreds of online options, how do you find the data analyst course that’s best for you?
Here is a checklist to help.
● Hands on projects using real world datasets
● Includes SQL, Python, Excel, and visualization tool
● Provides practice quizzes and assignments
● Includes a capstone project or portfolio-building portion
● Mentors or champions career-wise
● Comes from an accredited university or provider (e.g. Coursera, Udacity, edX)
As a novice yourself, focus on beginner-friendly data analytics courses that will ease you into gradually expanding your skillset.
Both have their place:
Free Courses: Perfect for experimentation and having a taste of the sector. Sites such as Coursera and Udemy, provide free trials or audit modes.
Paid Programmes: Include a curriculum, certification and sometimes the possibility of career support. Use these if you’re really serious about making a transition to a full-time position.
If you’re going to spend money, the course should have good reviews, industry projects, and a certification that employers recognize.
Final Thoughts: You Don’t Have to Be Brilliant—Just Consistent
It’s not rocket science and it doesn’t take unbelievable amounts of work, but it does take consistent work. Spend at the very least 5–10 hours a week learning, doing projects, and staying curious.
Whether you take a data analyst course to learn and transition into this role, or choose to get an assortment of data analytics courses from multi-platform sources, the most important thing is don’t wait and lose interest.
The world runs on data — and you can be the person who helps analyze and interpret it.
