I have a structured e-commerce dataset sitting in Excel/CSV format that needs a thorough exploratory data analysis. My goal is to turn raw tables into an insightful visual narrative—clear charts, concise commentary, and an executive-style report or interactive dashboard that highlights the key patterns hiding in the numbers. Here is what I need from you: • A clean, well-documented analysis (Python with pandas, seaborn/matplotlib or R tidyverse are fine) that walks through data profiling, outlier handling, and any necessary feature engineering. • Compelling visualizations—think sales trends, category performance, customer behaviour—that can be dropped straight into a slide deck or shared as an interactive report (Tableau, Power BI, or a notebook with embedded visuals). • A short written summary explaining the main take-aways in plain English, suitable for a non-technical stakeholder. Acceptance criteria 1. Reproducible code / notebook that runs end-to-end on the supplied CSV/Excel files. 2. At least five high-quality, well-labelled plots covering sales over time, top products, geographic or customer segmentation insights, and any surprising anomalies. 3. Final report or dashboard delivered in PDF, PPTX, or hosted interactive format, ready to present. If you’re comfortable turning e-commerce data into an engaging story, I’d love to see your approach and a couple of past visual pieces.