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Data Analyst with less than a year in SQL, Power BI, Python & AI tools
Computer Science Engineering graduate (CGPA: 8.75/10) with strong analytical and problem-solving skills. Proficient in Excel, SQL, and Power BI for collecting, analysing, and interpreting complex datasets. Experienced in creating dashboards and reports to support business decisions, identifying trends and growth opportunities, and ensuring data accuracy across systems. Familiar with Python and GenAI tools. Eager to contribute to data-driven strategies and business performance improvement.
CMR Technical Campus
B.Tech · Computer Science Engineering
August 1, 2022 – June 30, 2026
Student Behaviour & Cognitive Load Analytics
June 1, 2026 – Present
Analysed structured e-learning datasets applying data cleaning and feature engineering pipelines using Pandas to ensure data quality before analysis. Visualised prediction trends and accuracy metrics to deliver clear, actionable insights for platform decision-makers - supporting data-driven strategies for performance improvement.
Data Analysis & Reporting Dashboard
June 1, 2026 – Present
Cleaned, deduplicated, and validated large datasets using Python and Excel (pivot tables, VLOOKUP, formulas), significantly improving data accuracy across multiple sources. Wrote MySQL queries with complex joins and aggregations to cross-check data integrity and automate mismatch detection, reducing manual effort substantially. Built Power BI dashboards presenting data quality metrics and business trends, enabling decision-makers to identify patterns and act on clear visual insights.
Hospital Database Management System
June 1, 2026 – Present
Designed and managed a relational database for patient records - wrote complex SQL queries, joins, and aggregations ensuring data integrity and accuracy across systems. Presented the system at Project Expo, demonstrating proficiency in SQL-based data management and communicating analytical findings effectively to a panel audience.
Phishing Website Detection - Data Analysis & Trend Identification
June 1, 2026 – Present
Performed end-to-end data preprocessing on a structured dataset - handled missing values, outliers, and feature encoding using Pandas and Excel, achieving 97% model accuracy. Used SQL queries for data profiling and validation; produced tabular comparison reports to support business decisions on model selection - demonstrating interpretation of complex datasets. Identified key trends and patterns across website features to derive actionable recommendations, aligning outputs with business reporting objectives.
AWS Data Engineering
AWS Academy / Eduskills
June 1, 2026 – Present
Data Visualization
Infosys Springboard
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's academic projects show a diverse application of data analysis skills across different domains (e-commerce, healthcare, education). Participation in hackathons and competitive programming suggests a collaborative and growth-oriented mindset. The certifications in Data Visualization and AWS Data Engineering indicate a commitment to continuous learning and staying updated with industry tools, aligning well with a dynamic work environment.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical thinking, problem-solving skills, and attention to accuracy through competitive programming and project achievements. Their ability to present findings and communicate analytical insights, as noted in the 'Hospital Database Management System' project, suggests good communication skills. The academic projects indicate a proactive approach to learning and applying data analysis techniques.