1. Performed data cleaning, preprocessing, and transformation to ensure dataset accuracy and consistency. 2. Designed interactive dashboards with dynamic filters, drill-down analysis, and geographic mapping for accident hotspots. 3. Applied calculated fields, aggregations, and KPIs to track fatalities, injury rates, and vehicle involvement. 4. Conducted trend analysis across time, location, and accident severity using advanced Tableau features. 5. Delivered a scalable and user-friendly visualization tool for data-driven decision making.

Collected historical sales and revenue data from MySQL databases and external sources; cleaned and transformed datasets using Python and R. Conducted exploratory data analysis (EDA) to identify seasonal patterns, trends, and anomalies in sales performance. Built time-series forecasting models to predict future sales with high accuracy. Developed interactive Tableau and Power BI dashboards to visualize key metrics, including revenue trends, top-selling products, and regional performance. Provided data-backed recommendations for inventory planning, marketing strategies, and revenue optimization