How to become a data analyst: Did you know that 2.5 quintillion bytes of data are generated globally every minute? This isn’t just random numbers—it’s a goldmine of opportunities capable of transforming your career. When Manish graduated, he was burdened with significant debt. In just three months, without enrolling in any costly boot camps or holding a computer science degree, he self-taught data analytics and landed a high-paying job at a reputed firm.

Today, we’ll provide you with a detailed 3-month roadmap to becoming a data analyst. We’ll also recommend the best Hindi course for those looking to learn data analysis from experts. On Reddit, someone once expressed concern about job market competition.

An HR professional responded, stating that many candidates possess only basic skills and lack critical thinking or storytelling abilities. While there are numerous job opportunities, skilled professionals remain scarce. If you are interest to know how to become a data analyst in 3 months in detailed way, then you will have to read this article carefully till end, so without any further delay, let’s get started!

What is Data Analyst?

A data analyst is a professional who analyzes data to extract important information and trends. He collects and organizes data from various sources and helps in making useful decisions for the business. The role of a data analyst is very important in today’s digital age.

How to become a Data Analyst – Overview

Here we are going to provide you complete roadmap to become a data analyst in tabular form:

The Growing Demand for Data Analysts

The number of data-driven companies is rising rapidly. According to the US Bureau of Labor Statistics, demand for data analysts is expected to grow 36% from 2023 to 2033. Some worry that AI might replace data analysis jobs. However, AI tools like GPT cannot entirely replace human data analysts. Companies handle datasets with millions or billions of parameters that require precise processing and analysis.

Even if AI becomes highly capable, decision-making and problem-solving in data analysis require human expertise. While AI can automate repetitive tasks like data cleaning and querying, extracting insights, making business recommendations, and telling compelling stories remain human-driven tasks. Think of AI as a productivity-enhancing tool like Excel—it aids the process but doesn’t replace human intuition.

Why You Should Follow This Roadmap?

This roadmap is tested and proven. Whether you are a student, fresher, or working professional seeking a career switch, you can confidently follow this guide to become a data analyst without any coding background. Now, let’s dive into the step-by-step process.

Step 1: Master Excel Functions (Week 1-2)

Start by learning essential Excel functions such as Search, VLOOKUP, HLOOKUP, Pivot Tables, and Charts. Additionally, focus on cleaning, sorting, and organizing data within a single file.

Step 2: Learn SQL (Week 3-4)

SQL (Structured Query Language) is crucial for accessing and manipulating data from databases. Practice basic SQL commands like SELECT, UPDATE, DELETE, and JOINS on platforms like Mode Analytics and SQL Zoo. Mastery of SQL will enable efficient data analysis.

Example: Imagine an e-commerce company needs data on customers who shopped more than five times last month. You can easily retrieve this information using a simple SQL query.

Step 3: Enroll in a Comprehensive Hindi Data Analysis Course

We recommend a structured 90-day boot camp designed by industry experts. This course covers everything from beginner to advanced levels, ensuring you become job-ready without needing additional training. Led by experienced data scientist Krish Singh, an IIT Delhi alumnus, the course offers real-world industry projects, practical learning, class notes, and assignments.

Key Benefits:

• Master core job skills like Python.
• Access industry-level projects
• Get job assistance and verified certificates (including IBM’s Data Analytics certification)

If you are really concern about to become a data analytics in just 3 months then you can use this course to master your proficiency by below given link:

Step 4: Learn Python for Data Analysis (Week 5-6)

Python is a must-have skill for data analysts. Platforms like PythonAnywhere and Anaconda2 offer tools for statistical analysis, which enhances your ability to derive meaningful insights.

Step 5: Master Data Visualization (Week 7-8)

Data visualization helps present complex insights through graphs and charts. Learn tools like Tableau and Power BI. Free courses on YouTube can help you get started.

Example: Financial services companies use Power BI to visualize data trends. Presenting sales growth and expenses visually enables leaders to make data-driven decisions quickly.

Step 6: Understand Basic Statistics and Probability (Week 9-10)

Basic knowledge of statistics is essential for accurate decision-making. Focus on concepts like mean, median, mode, standard deviation, and probability. Learn these topics practically to solve real-world problems.

Example: A company launching a new product can use probability concepts like confidence intervals and hypothesis testing to predict its market performance.

Step 7: Explore Machine Learning Basics (Week 11)

For advanced roles, understanding machine learning basics is beneficial. Machine learning helps identify patterns and build predictive models. Algorithms like decision trees and logistic regression can analyze customer data and provide accurate predictions.

Step 8: Build a Portfolio and Resume (Week 12)

In the final phase, focus on building a strong portfolio. Complete data analysis projects on platforms like Kaggle and GitHub. Also, prepare for interviews by reviewing common data analyst questions on platforms like Glassdoor.

Note: Invest time in practice projects and mock interviews to boost your job prospects.

Additional resources to become a Data Analyst

• Free Learning Platforms: YouTube, Coursera, and edX
• Practice Platforms: Kaggle, GitHub, and Mode Analytics
• Community Support: Join forums and LinkedIn groups for networking and support

Data Analyst Salary

The salary of a data analyst depends on their experience, skills and company. In India, a fresher data analyst earns an average of Rs 4 to 6 lakh per annum, while experienced professionals can earn Rs 10 to 15 lakh or more. Salaries are higher in big cities.

Data Analyst Interview Questions

Here we are going to provide you some basic interview questions of Data Analyst but if you want to master it then you can follow the above given resources:

Q 1: What do you think is the job of a data analyst?

Ans: The purpose of this question is to get the candidate to understand the role and responsibilities of a data analyst.

Q 2: What tools are used in data analysis?

Ans: The purpose of this question is to know what kind of data tools the candidate knows, such as Excel, SQL, Python, Tableau, etc.

Q 3: How to write a data query using SQL?

Ans: This question is asked to test the knowledge of SQL to see if the candidate has the ability to extract data from a database.

Q 4: What kind of data cleaning and preprocessing do you have experience with?

Ans: Data cleaning and preprocessing are very important steps, this question checks whether the candidate understands the process or not.

Q 5: What analytical techniques did you apply in your previous project?

Ans: Here, the candidate gets a chance to talk about his previous experience, where he can give details of the techniques used to analyze the data. How do you identify hidden patterns or trends in a data set?

This question tests whether the candidate has the ability to identify deeper patterns and trends in data.

Q 6: What tools do you use for data visualization?

Ans: This question is asked to find out which tools the candidate uses to visually present data, such as Tableau, Power BI, or Python libraries (Matplotlib, Seaborn), etc.

Data Analyst Resume

In a data analyst resume, it is important that you present your skills, experience, and qualifications in an effective manner. Here is the structure of a typical data analyst resume:

Name and contact details

• Full name
• Phone number
• Email ID
• LinkedIn profile or personal website (if any)

Objective

This is where you briefly state your career goal and your desire to work as a data analyst. Example:

“As a data analyst, I use my analytical skills and technical knowledge to solve company data-related problems and improve business decisions.”

Skills

• Data analytics tools: such as Excel, SQL, Python, R, Tableau, Power BI
• Data processing and cleaning
• Statistics and analytical thinking
• Data visualization
• Reporting and data modeling
• Communication and teamwork

Education

• Degree, university name, year
• Example: B.Tech (Computer Science), ABC University, 2019

Work Experience

Here you list your previous work experience, including what responsibilities you performed as a data analyst and what projects you worked on. Example:

• Data Analyst, XYZ Company, 2022-2024
• Collecting, processing, and analyzing data
• Creating reports and visuals for clients
• Solving data-related problems using SQL and Python

Certifications

Examples: “Data Analytics Professional” (Coursera), “Python for Data Science” (Udemy)

Projects

You can mention your personal or professional projects in which you have used data analytics. Example:

• “Customer Data Analysis and Reporting for XYZ Company”
• “COVID-19 Data Analysis and Prediction Models”

Languages

• Hindi (Mother Tongue)
• English (Fluent)

This is a general resume structure, which you can customize based on your personal information.

Wrapping Up

✅ Congratulations! 🎯 You now have a clear and actionable 3-month roadmap to become a data analyst, even without a coding background. From mastering Excel and SQL to diving into Python, data visualization, and machine learning basics, this step-by-step guide equips you with the essential skills and tools needed to land a high-paying job in the data analytics field.

💡 Key Takeaway:
The demand for skilled data analysts is only going to increase in the coming years. By following this proven roadmap, building a strong portfolio, and practicing regularly, you’ll be well-prepared to stand out in the job market.

🔥 What’s Next?
If you’re eager to explore more career-enhancing guides, expert tips, and industry insights, make sure to check out our latest articles on 👉 techgrosir.com. Whether you’re looking for in-depth tutorials, job updates, or productivity hacks, we’ve got you covered. 🌟

👉 💻 Keep learning, keep growing, and take your career to the next level with TechGrosir!

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