How to Become a Data Analyst in 2025: Step-by-Step Career Guide
Data analytics is one of the most sought-after future-proof careers in India. According to a 2024 report by the Times of India, the country has the highest demand for data analytics jobs worldwide, and the industry has only seen a surge in recent years!
With the rapid digitization of different sectors and AI integration across industries, India has witnessed a 65% increase in AI-related job roles since 2019, and the numbers are only expected to grow further. This is a great time to nurture that interest and learn data science to explore highly lucrative career options.
Keep reading to understand what data analytics is and discover how to become a data analyst in 2025.
What is Data Analytics?
Data Analytics is a set of steps professionals perform to figure out patterns, identify market and consumer behavior trends, and draw conclusions based on detailed reports.
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It facilitates trend forecasting and data-driven decision making and helps businesses and organizations maximize their RoI.
Data analysis includes data collection, cleansing, organizing, and structuring vast data sets, and using statistical and mathematical tools and machine learning techniques to find out interrelationships.
What Does a Data Analyst Do?
Data analysts collaborate with the operations, marketing, and finance teams to ensure a hassle-free workflow, streamlined processes, and help draft informed business strategies.
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They gather data from various sources – web, databases, surveys, etc. – and correct any errors, ensuring data consistency.
Data analysts conduct a thorough inspection of the data available to them to spot any trends and patterns and prepare conclusive and actionable reports.
A Step-by-Step Guide on How To Become A Data Analyst in 2025
- Key Skills To Become A Data Analyst
Want to know if you possess the right skills to become a data analyst and get into a premium institute of your choice? Here are some of the key technical and non-technical skills that you need to ensure a thriving career.
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- Technical Skills
- Familiarity with Programming Languages
Familiarity with programming languages is a must for any aspiring data analyst. While a basic understanding of R and SQL is a plus, make sure you are acquainted with Python, Java, and C++.
- Mathematical and Statistical Competency
A strong foundation in statistics and mathematics allows data analysts to study, structure, interpret, and analyze data more efficiently.
Understand how and where mathematical and statistical tools are used in data analysis, and learn different methods you can incorporate for different data types.
- Data Handling
Data handling covers all the different steps you go through when gathering and analyzing data. This includes familiarity with the sources of data collection, data cleaning, data visualization techniques, and the basics of data analysis.
It is central to the job roles of any data analyst. While you are not expected to be an expert in identifying sources and analyzing complex data at this stage, knowledge of methods, software, and steps is a must to secure higher ranks in the entrance tests and enroll in a premium institute.
- Machine Learning
Machine learning helps identify patterns and get precise insights out of large datasets.
To start your journey in data analytics, make sure you have a basic understanding of predictive modeling, automation, and pattern recognition techniques crucial in the data interpretation process.
- Understanding of Relevant Software
Data analysts rely on various digital tools and software for tasks like data structuring, visualization, and more. A deep understanding of tools like Excel and Tableau is crucial to becoming a data analyst.
Leverage online tutorials to get familiar with their UI and functions to get a head start in your course.
- Soft Skills
- Critical Thinking and Problem Solving
As a data analyst, you need to have strong problem-solving and critical thinking skills to identify business problems, analyze data sets according to context, and make informed decisions.
It also reduces the chances of errors in data processing and interpretations.
- Communications
Data analysts work in teams. This requires effective communication within the teams and with other internal (marketing, finance) and external (clients) teams that might be involved in a project.
Effective communication ensures a smooth workflow, reduces conflicts, and promotes accurate analysis and applications.
- Attention to Detail
An eye for detail is an important quality for anyone working with vast datasets, where even minute errors can potentially alter results.
Detail-oriented approaches minimize errors, help draw effective conclusions, and prepare more precise and legible reports for further processing.
- Data Analytics and Data Science Courses
If you want to work as a data analyst, pursuing a bachelor’s degree in data analytics or data science is the first step towards your career.
Start by shortlisting the colleges and courses of your choice, and filter out the right ones based on accreditation, location, alumni base, fee, structure, curriculum, and other factors.
- Eligibility
Most data analytics and data science courses require you to complete your 10+2 from a recognized board with a science stream.
You must have mathematics as one of the core subjects in the 12th, and a minimum overall score of 55% or an equivalent GPA.
- Entrance Test
Institutes offering data science and data analytics courses typically allot seats based on entrance tests, personal interview, score of +2, or a combination of these.
Some of the major entrance tests include CUET (UG), SET, and AAFT GEE. Watch out for the application forms so you don’t miss the deadlines!
- Course Overview
Take a look at the table below for a detailed insight into the different courses you can pursue after school and the areas they cover.
These courses span 3-4 years and are designed to acquaint you with the industry tools, current trends in the industry, core areas of the discipline, internship opportunities, and scope to develop a strong portfolio.
| Course Title | Subjects Covered |
| B.Sc in Data Science | Foundation and Principles of Data ScienceStatistics and Mathematics for Data ScienceUnderstanding Data Collection, Acquisition, and DatabasesTools, Methods, and Applications in Data ScienceProgramming LanguagesAI and MLDeep LearningData Mining and Data WarehousingCloud Computing and Big Data Storage |
| B.Sc Data Analytics | Basics of Data Science and AnalyticsUnderstanding Data Structures and Methods of Data CollectionProgramming Languages (Python, SQL, and R)Data Mining and Database ManagementStatistical and Mathematical Tools for Data AnalysisData Visualization TechniquesBig Data Storage and Analysis |
| B.Sc Artificial Intelligence | Introduction to AIProgramming Languages and Computational Techniques for AIUnderstanding Advanced AI ModelsAI Algorithm and Machine LearningCloud TechnologyVector DatabasesNatural Language ProcessingAI Model DevelopmentUnderstanding Generative AI and AI WorkflowsAcquainting with Azure, AWS, EDGE AI, and GCPApplication of AI in Different Sectors |
| B.Sc Computer Science | Programming: Basic and Advanced Programming LanguagesComputer Systems and NetworksData CommunicationDatabase Management SystemsAI and MLInformation SecurityStatistical and Mathematical Foundation Data MiningNumber Systems and CodesUnderstanding Embedded Systems |
- Average Fees for Data Science Courses
Course fees for data science, data analytics, and other related courses often vary between private and public institutes, their location, infrastructure, ranking, and other factors.
However, the average fee lies around ₹1,50,000 – ₹7,50,000 for bachelor’s degree courses.
- Apply For Internships
Most professional courses include internships in their curriculum. You can also look for additional opportunities through professional networking platforms like Internshala and LinkedIn.
Getting in touch with alumni, networking within student communities, and participating in competitions, workshops, and seminars will enhance your chances of securing an internship and getting some hands-on experience in the industry.
- Building A Portfolio for Data Analyst Jobs
Use Platforms like LinkedIn and GitHub to add and showcase different projects using a variety of formats.
Start your portfolio with a brief “about me” section that covers –
- Why did you choose Data Analytics
- Your Specialized niche
- Your interests and expertise within data analytics
Ensure your portfolio has different types of projects that reflect your versatility –
- Use different tools (Excel, Tableau) and Programming Languages (Python, R, SQL) to show your proficiency.
- Include detailed projects on data cleaning and data visualization.
- Don’t forget the projects where you have collaborated with others to showcase your teamwork skills.
- Write a short blog/article explaining complex data cleaning, processing, or analysis steps.
- Include 1-2 data analysis projects using different methods.
- Attach tiny concept notes to ensure the recruiter is on the same page as you.
- Networking and Applying for Data Analyst Roles
Make sure you are leveraging the networking platforms, keeping in touch with the official alumni groups, and maintaining the professional relationships you have built throughout your university life.
Join online communities and data analyst forums to make the best out of the available resources.
Watch out for any new vacancies, update your resume according to the role you are applying for, and draft a job-specific cover letter to maximize your chances of getting a call and landing a well-paid job.
Popular Data Analytics Jobs in India and How Much Salary to Expect
Salaries in data analytics jobs may vary based on job requirements and companies. However, you can expect a salary between ₹3LPA – ₹7LPA as a fresher.
| Job Titles | Entry-Level Salary (₹) Per Year |
| Junior Data Analyst | 3,50,000 – 6,00,000 |
| Financial Analyst | 3,00,000 – 7,00,000 |
| Marketing Analyst | 3,00,000 – 6,00,000 |
| Business Analyst | 3,00,000 – 7,00,000 |
Frequently Asked Questions (FAQs)
How do I become a data analyst after 12th in India?
To become a data analyst after 12th, pursue a bachelor’s degree in data science, data analytics, or computer science with Mathematics as a core subject. Entrance exams like CUET or AAFT GEE may be required.
What qualifications are needed to become a data analyst in 2025?
You need a 10+2 qualification with Mathematics, and a bachelor’s degree in data science, analytics, or a related field. Skills in Python, SQL, statistics, and data visualization are essential.
Which course is best for becoming a data analyst?
Top choices include B.Sc in Data Science, B.Sc in Data Analytics, and B.Sc in Computer Science, offering training in tools like Python, SQL, Tableau, and machine learning techniques.
What is the average salary of a data analyst in India in 2025?
The average starting salary for data analysts in India ranges from ₹3 LPA to ₹7 LPA, depending on skills, industry, and company. Advanced skills can lead to higher packages.
Can I become a data analyst without coding?
Yes, you can start with tools like Excel, Tableau, and Power BI, but for long-term success, learning coding languages like Python or SQL is recommended to handle complex data sets.
Conclusion
Data analytics is a highly lucrative career. Understanding how to become a data analyst and learning about the various online and offline courses available can truly transform your career and open up a multitude of new opportunities.
It is an evolving field that requires constant skill upgrades and fresh talent to be recruited across industries to keep up with the dynamic changes and incorporate trends to make informed data-driven choices that would boost the RoI and help businesses grow.
AAFT offers comprehensive data science courses that will help you access industry-standard tools and resources, learn from the experts, and get a hands-on experience so you can smoothly navigate the professional realm.
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