🎯 Aspiring Data Analyst | Passionate about storytelling through data | Skilled in Power BI, Python, SQL, and Excel
✅ B.Tech in Computer Science (2021–2025), MIET, Meerut

I'm a detail-oriented data analyst with hands-on experience in real-world projects involving data wrangling, visualization, and predictive analytics. I enjoy using tools like Power BI, Python, and SQL to uncover insights and help drive data-driven decisions.

I aim to work as a Data Analyst, helping companies make data-driven decisions through actionable dashboards, powerful analysis, and storytelling through data.

• Explored Amazon sales data to uncover trends in revenue, customer behavior, and product performance.
• Built interactive dashboards using Power BI with custom visuals and slicers.
• Applied DAX functions and created data models to enhance report usability and insights.

Tools: Power BI, DAX, Data Modeling, Data Visualization

• Developed a computer vision-based invisibility cloak using Python and OpenCV to simulate an invisibility effect.
• Captured the static background and applied color detection to mask the red cloak.
• Replaced the masked region with the background to create a real-time cloak effect.

Tools: Python, Matplotlib, NumPy, OpenCV

• Explored agricultural datasets to analyze sugarcane production trends across regions.
• Conducted data analysis in Jupyter Notebook, visualized patterns using Matplotlib and Seaborn.
• Focused on identifying top-performing states and yield improvements.

Tools: Python, Pandas, Matplotlib, Seaborn

• Analyzed music store data to uncover top-selling artists and revenue by genre.
• Wrote optimized SQL queries to clean and analyze transactional data.
• Suggested improvements for stock and inventory management.

Tools: SQL, Data Cleaning, Joins, Subqueries

• Performed EDA on large-scale sales data to identify purchase behavior by customer segments.
• Built machine learning models to predict user purchases for better targeting.
• Used pandas, NumPy, and scikit-learn for analysis and prediction.

Tools: Python, Pandas, NumPy, Machine Learning

• 📈 Analyzed daily sales data of a bakery to identify peak hours, popular products, and seasonal trends
• Used Pivot Tables, VLOOKUP, and conditional formatting for clean insights
• Built a clean dashboard to display total sales, top 5 products, and hourly performance

Tools: Microsoft Excel, Pivot Tables, Charts, Data Cleaning

• 📦 Analyzed online sales data to track performance metrics like revenue, order volume, and customer retention
• Wrote SQL queries using joins, aggregations, and window functions to extract KPIs
• Identified best-selling products, top customer regions, and monthly sales trends

Tools: SQL, PostgreSQL, Data Cleaning, Analytics Queries

• ✅ AWS Cloud Practitioner
• 📊 Data Analytics Course – ICT Academy & Infosys (Aug–Sep 2024)
• 🤖 AI & Machine Learning Internship – EduSkills (Jul–Sep 2024)

• 🔗 LinkedIn
• 📧 Email
• 🗂 GitHub Projects
• 🔗 Hackerrank
• 📄 My Resume

✨ Thanks for visiting! I’m always learning and open to collaboration on exciting data projects!