
Analyzing sales and business datasets to identify trends, performance patterns, and actionable insights that support data-driven decision-making.
Writing SQL queries using joins, filters, aggregations, and subqueries to analyze sales, rental, and transactional data and answer business questions.
Creating interactive dashboards and reports with charts, filters, and KPIs to track sales performance, revenue trends, and operational metrics.
Using Python for data cleaning, exploratory data analysis (EDA), and basic automation, supporting analytical workflows and reporting tasks.
