Programming
What do you need to learn to become a Data Analyst?
Oct 27, 2025
3-4 min Reading time
A data analyst is someone who uncovers the stories behind the numbers. He or she analyzes the data
It helps businesses make the right decisions by collecting, cleaning, and analyzing data. The job of a data analyst is not just to work with statistics, but also to make these numbers meaningful.
Data analytics identifies trends, uncovers problems, and predicts the future.
predicts. Thus, raw data becomes a strategic power. With the acceleration of digital transformation, the demand for data analysts in many fields has increased dramatically.
Your path to entry and sustainable growth in this field in 2025 should include fundamental knowledge and tools for the world of data analytics.
1. Education and Data Literacy
To become a data analyst, it is important to first become familiar with the field of information and statistics. Data literacy, that is, the ability to read, understand, analyze and translate information into conclusions, is the main foundation of data analysts. Formal education, such as bachelor's programs in computer science, business, statistics or data science, also systematically forms this foundation, along with analytical thinking.
2. Technical Skills: SQL&Open source
The SQL programming language for accessing databases and writing queries is essential for every data analyst. However, in addition to SQL, other programming languages for statistics and data processing, such as Python or R, should also be learned, as they provide data analysts with a wider range of analysis, data cleaning, and visualization capabilities. Since R and Python are open source, anyone can learn and use these languages for free. These languages have a large user community and rich library support, which provides flexible and powerful tools for data analysis.
For modern data analysts, R and Python allow for easy application of advanced techniques such as both statistical analysis and machine learning.
3. Statistical Knowledge and Data Visualization
Qualitative statistical indicators such as averages, probability, hypothesis testing, etc.
It helps the analyst to draw the right conclusions in the work process. In addition, the ability to convert dashboards and visualized graphs to put the analysis results into an understandable form is also important. Tools such as Power BI and Tableau are at the forefront here.
4. Data Cleaning and Preparation
User experience shows that the cleaning process accounts for 80% of the analysis. Thorough cleaning and preparation are essential. This is a key stage in the real work of a data analyst. Microsoft Learn also emphasizes that an analyst should perform data profiling and transformation operations.
5. Critical Thinking and Soft Skills
Technical knowledge alone is not enough to become a data analyst. Analytical thinking, critical analysis, empathy, and ethical responsibility are also important. The widespread use of AI (artificial intelligence) systems in the data world brings ethical thinking and the human factor to the fore. It is also very important for a data analyst to convey information to others in a simple and effective way. Learning all these tools and approaches systematically is necessary to find your place in the world of data analytics. This field is dynamic and constantly updated, which means that the learning process for a data analyst never ends.
If you are just starting out and plan to become a professional data analyst, start with simple tools, progress gradually, and gain experience working with real data. Data-driven thinking skills will be needed everywhere in 2025 and beyond.
If you want to become a data analyst, you must have these skills:
· Data literacy and correct analytical thinking;
· SQL, Python/R knowledge;
· Statistics and data visualization;
· Data cleaning capability;
· Analytical thinking, ethics and communication skills.
Building a solid foundation for this combination will help you succeed in both becoming a data analyst and in other analytical roles.
By studying the Data Analytics curriculum taught at Code Academy, you will gain both theoretical and practical skills. Moreover, by working on real projects, you will take the first steps towards becoming a powerful data analyst of the future.
Becoming a professional Data Analyst of the future is in your hands.
