Sum Raghav

I’m a detail-oriented Data Analyst with hands-on experience building end-to-end analytics projects using Python, SQL, and business intelligence tools. I enjoy transforming messy data into clear, decision-ready insights for real business contexts.

I’ve built three portfolio projects across e-commerce, telecom, and retail—analyzing messy datasets, engineering features, and validating results with statistical and ML techniques. In telecom churn analysis, I identified key churn drivers and built a Logistic Regression model achieving 82% accuracy in predicting churn.

For customer behavior, I developed an e-commerce intelligence suite using SQL (JOINs, CTEs, Window Functions) and Python to analyze 100K+ orders, then applied RFM segmentation to flag customers at risk or needing attention. I also connected operational metrics (like delayed deliveries) to customer outcomes and supported recommendations such as regional warehouse expansion.

In retail sales analysis, I created a Power BI dashboard to track revenue trends and category performance, and delivered actionable recommendations to improve inventory allocation and marketing prioritization. I’m self-driven in learning—through SQL certification, Kaggle practice, and self-taught Power BI with project implementation.