🎯 Aspiring Data Analyst with hands-on experience in analyzing data, building dashboards, and extracting meaningful insights using modern data tools
- Programming & Querying: Python, SQL
- Data Analysis: Data Cleaning, EDA, ETL
- Visualization: Power BI, Tableau
- Spreadsheets: Advanced Excel
- Soft Skills: Analytical Thinking, Problem Solving, Communication
🔹 Insurance Dashboard
🔹 Adventure Works Cycles
🔹 CRM Analytics
🔹 Real-Time People Tracking & Counting System
🔹 Power-Optimized 3-Stage Pipelined RISC-V Processor
🔹 Parking Sensor using Arduino
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Bachelor of Technology (B.Tech) - Electronics and Communication Engineering (March 2025)
Gayatri Vidya Parishad College of Engineering (Autonomous), Visakhapatnam, Andhra Pradesh. -
Intermediate - MPC
Sri Chaitanya Junior College, Vizianagaram, Andhra Pradesh.
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Data Analyst Internship - Aivariant (Jul 2025 - Apr 2026)
- Completed a structured Data Analyst internship, working on real-world datasets and analytical problem statements.
- Applied SQL, Python, and Advanced Excel to extract, clean, and analyze data for meaningful insights.
- Performed data preprocessing and exploratory data analysis (EDA) to identify trends and patterns.
- Developed interactive dashboards and reports using Power BI / Tableau to support decision-making.
- Strengthened analytical thinking, problem-solving, and professional reporting skills through hands-on tasks.
📄 Certificate
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Data Analyst - ExcelR (Dec 2025)
- Gained hands-on experience in SQL, Python, Advanced Excel, Power BI, and Tableau for data analysis and reporting.
- Performed data cleaning, preprocessing, and exploratory data analysis (EDA) to identify trends and patterns.
- Developed interactive dashboards and KPI reports to support data-driven business decisions.
- Applied ETL processes to transform and model raw data into structured, analysis-ready datasets.
- Strengthened analytical thinking, problem-solving, and communication skills through real-world case studies and projects.
📄 Certificate
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Python 101 for Data Science – IBM Cognitive Class (Jun 2025 - Aug 2025)
- Learned Python fundamentals for data science, including variables, data types, loops, functions, and control structures.
- Worked with Python libraries such as NumPy and Pandas for data manipulation and analysis.
- Performed data loading, cleaning, and basic exploratory analysis using Python.
- Implemented data processing and transformation techniques on structured datasets.
- Strengthened problem-solving and analytical skills by applying Python to real-world data science exercises.
📄 Certificate