About Me
Data Analyst skilled in SQL, Power BI, Excel, and Python experienced in building dashboards and performing trend analysis on 100K+ datasets to support business decisions.
Experience
Data Analyst
Collaborated with Sports Authority of India(SAI) and 10+ sports federations to collect, validate, and manage athlete participation, tournament, and medal data for audit and compliance reporting. Cleaned and transformed 50,000+ sports records using Excel and SQL, improving data accuracy by 30% and reducing reporting errors during SAI audits. Built interactive dashboards and MIS reports to monitor athlete participation, medal trends, and federation performance, enabling stakeholders to generate insights and reduce manual effort by 40%.
Data Analytics Intern
Analyzed health and fitness data by developing SQL queries to generate over 30 metrics across 4 different environments, using advanced techniques such as window functions and date functions on Metabase. Created complex SQL queries to extract insights on users’ medical histories, subscription details, plan-wise metrics, and professional consultations by joining multiple tables. Worked on key performance indicators (KPIs) such as paid users, total users under each dietician and doctor, user weight, and city-wise user counts, driving actionable insights to improve business operations. Utilized Excel for data analysis and reporting, applying advanced formulas like SUMIFS, COUNTIFS, VLOOKUP, and pivot tables to enhance data accuracy and support decision-making processes. Improved reporting efficiency by automating key data processes and generating user-friendly dashboards to provide real-time metrics for various stakeholders.
PROJECTS
Zomato-Data-Analysis
The Zomato Data Analysis Project is a data-driven case study where restaurant and food delivery data is analyzed to generate meaningful business insights. The project involves loading and managing Zomato dataset tables and using SQL queries to explore customer behavior, restaurant performance, order patterns, ratings, and spending trends. Through data cleaning, filtering, joins, and aggregation techniques, raw data is transformed into useful insights that help understand how customers interact with restaurants and how different factors impact business performance. Overall, this project demonstrates strong SQL skills and the ability to solve real-world business problems using data analysis.