Failed 12th Grade? How to Become a Data Analyst in 2025 – Skills & Steps You Need to Succeed
Data is everywhere, and companies need qualified individuals to interpret it. If you’re interested in this field, enjoy solving issues, and love discovering answers, you can become a data analyst regardless of your educational background. You simply need to be open to learning. Everything you need to get started will be covered in this guide, which will cover:
- What is data analytics, and why should we use data analytics?
- The steps to become a data analyst, even without a degree
- Challenges faced by a data analyst
Failing a grade does not mean it’s the end; it just means that you have only just begun your journey and are on the path of trying out expected adventures to reach your goal.
Let’s talk about how you can change your situation and pursue a fulfilling career in data analytics!
Must Read: Best Data Analysis Techniques You Must Know in 2025
Why Should You Pursue Data Analytics?
Every click, purchase, and social media contact generates vast amounts of data every second, flowing from businesses, governments, and individuals. However, raw data alone is worthless. This is where data analysis comes in.
Data analytics helps businesses in retail, healthcare, sports, finance, etc., make better business decisions. This field is all about making a difference in the real world.
- Law enforcement organizations employ analytics to solve crimes.
- Environmental scientists rely on climate data to anticipate shifts in temperature, precipitation, and sea levels.
- Governments utilize data to monitor and stop disease outbreaks.
As data multiplies, companies that fail to adapt will struggle to compete. Understanding analytics provides an edge—whether launching a business, switching careers, or entering the job market. The rise of AI won’t eliminate the need for analysts. It will expand their role, increasing both their reach and their influence.
Must Read: What is Predictive Analytics
Become a Data Analyst in Just 5 Steps
Becoming a professional data analyst isn’t about knowing everything at once. It’s about knowing where to start. These steps will get you moving in the right direction.
Step 1: Why Should You Pursue Data Analytics?
Before we get started, let us define what a data analyst exactly does. To explain easily, a data analyst tries to solve the problems a business gets. They gather data, clean and process the data, and interpret the resulting data to find solutions to the problems.
Step 2: Develop the Right Skills
To become a data analyst, you will need specific tools and data skills. If you are a beginner or just starting, don’t worry! Everyone at some point in their life was at your place, and they learned all the right skills. Here’s how you can do it too:
1. Technical Skills
Working as a data analyst requires a range of technical skills that help with data gathering, cleaning, analysis, and visualization.
- Mastering Excel or Google Sheets will provide you with a strong basis for learning formulas, pivot tables, and data-cleaning techniques because many companies still manipulate data using spreadsheets.
- R and Python are must-have skills for aspiring data analysts, enabling them to analyze datasets, automate workflows, and apply machine-learning techniques to uncover trends and drive data-backed decisions.
- Power BI and Tableau are the most commonly used data visualization tools that assist in converting uninterpreted data into insightful understandings and simplifying your findings.
Also Read: Python Interview Questions for Data Analytics
2. Data Analytical Skills
- Critical thinking: Data Analysis is all about asking correct questions and finding the answers to them. Evaluating data sources, spotting biases, and arriving at trustworthy conclusions is essential.
Problem-solving: Problem-solving helps data analysts interpret data efficiently, spot trends and patterns, and get significant insights to deal with business problems.
3. Soft Skills
For data analysts to effectively communicate complex data insights, recommendations, and conclusions to stakeholders, communication is essential. This ensures that their analysis is understood and implemented and eventually leads to well-informed business decisions.
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Step 3: Select Your Learning Path
There is no defined path to becoming a data analyst, but you can choose whatever suits you best.
1. Self-study
Today, there are many free as well as paid courses available in the field, so you can choose any course and start studying by yourself. Learning platforms such as IFACET IIT Kanpur provide beginner-friendly courses in data analytics and programming.
Advanced Certification in Data Analytics (Self-Paced): Enroll Today
2. Online courses
Programs such as IFACET IIT Kanpur’s Data Analytics Program offer defined learning courses and hands-on projects. These courses are meant to get you from novice to job-ready in just a few months.
Professional Certificate Course in Data Analytics and Generative AI: Enroll Today
Predictive Business Analytics for Decision Making: Enroll Today
Advanced Certification in Data Analytics (Live Online): Enroll Today
3. BootCamps
If you prefer a more intensive approach, try attending a data analytics boot camp. These programs are fast-paced and frequently incorporate career services.
4. Certifications
Earning a certification can help you with increased job opportunities, higher earning potential, and professional development. Look for programs that validate your skills in relevant areas to future employers, such as the IFACET IIT Kanpur Certification in Data Science.
Step 4: Gain Practical Experience
Learning the theory is crucial, but nothing beats practical practice. Here’s how you can begin developing your portfolio:
- Work on your projects: Analyze data from your favorite sports team, monitor your finances, or look into public databases.
- Volunteer: Offer to evaluate data for small businesses or non-profit organizations.
- Internships: Look for entry-level positions or internships to obtain valuable practical experience.
Remember that your portfolio is your proof of ability. It’s what will differentiate you in a competitive job market.
Step 5: Network and Apply for Jobs
Networking is critical to securing your first job. Here is how to start:
- Join online communities. You can consider joining platforms such as LinkedIn and Kaggle, as they have active data analytics communities.
- Meetups and webinars conducted by IFACET IIT Kanpur are excellent opportunities to meet with industry professionals.
- Leverage social media: Share your projects and thoughts with LinkedIn to demonstrate your knowledge.
When looking for jobs, personalize your resume to highlight your abilities and initiatives. Don’t be afraid to start small—entry-level positions such as data analyst intern or junior data analyst can serve as stepping stones to larger prospects.
Conclusion
Data analytics is a field that values skills above degrees, and with the right approach, you can thrive in it.
Let’s be honest: this path will not be easy. You may have moments of self-doubt, technological difficulties, or rejection. But here’s the thing: every successful data analyst has been where you are now.
Struggling with basics? Begin with the basics and progressively increase your confidence. Do you feel overwhelmed by coding? Break it down into smaller, more achievable steps. Are you facing rejection? Use it as an incentive to further your abilities.
The trick is to keep going. Progress may be gradual, but each step puts you closer to your objective.
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