1) E-commerce Data Analysis (Target Brazil Dataset)
Scaler – Data Science & Machine Learning Program
Tools used: SQL (BigQuery), Analytical SQL, Window Functions, CTEs, Date-Time Analysis
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Project Description:
- Executed end-to-end e-commerce data analysis on 100K+ records using SQL in BigQuery, leveraging CTEs, window functions, and time-based aggregations.
- Generated actionable insights on sales growth, regional performance, logistics efficiency, and payment behavior to support data-driven business decisions.
- Identified delivery delays, freight cost inefficiencies, and seasonal demand patterns, proposing measurable optimization strategies.
- Insights simulated potential optimization opportunities across high-freight states and late-delivery regions impacting ~6% of total orders.
🔗 Project Link: https://docs.google.com/document/d/1-hVHwyVGxQDRmI4blEFBZrAd8JY5wgkNk6YUG_FZ59g/edit?tab=t.0
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2) E-commerce Dashboard & Data Visualization – Tableau
Scaler – Data Science & Machine Learning Program
Tools used: Tableau, Interactive Dashboards, Data Storytelling, Filters & Calculations
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Project Description:
- Developed an interactive Tableau dashboard analyzing e-commerce performance metrics including sales, profit, product categories, regional comparisons, and trend analysis.
- Implemented calculated fields, filters, and interactive controls to enable stakeholder-driven exploration and data-driven decision support.
- Published dashboard on Tableau Public to highlight end-to-end visualization and analytical storytelling skills.
🔗 Project Link: https://public.tableau.com/views/SuperstoreInteractiveDashboard_17599224591510/Dashboard1?:language=en-US&:sid=&:redirect=auth&:display_count=n&:origin=viz_share_link