● Wrote 15+ SQL queries to analyze 9,000+ Netflix titles across countries, genres, ratings, and directors. ● Built interactive Power BI dashboard with KPI cards, line chart, bar charts, donut chart, and treemap. ● Identified key insights: US leads with 3.2K titles, TV-MA most common rating, content peaked 2019-2020. ● Applied Power Query for data cleaning and DAX measures for custom calculations.

● Analyzed 1,000+ coffee sales transactions across countries, coffee types, and customer segments using Advanced Excel. ● Used XLOOKUP formulas to link order, customer, and product data across multiple sheets. ● Applied Pivot Tables, Slicers, and Timeline filters to build a dynamic and interactive analysis. ● Identified United States as top market ($35,638 in sales), surfaced top 5 customers by revenue.

● Performed end-to-end EDA on a telecom customer dataset to identify key churn drivers. ● Cleaned and preprocessed raw data using Python (Pandas) to ensure accuracy. ● Created visualizations including charts, heatmaps, and statistical summaries using Matplotlib and Seaborn. ● Published complete project with documentation on GitHub.