I have a raw customer dataset and need a clear, reliable descriptive analysis that turns those rows and columns into actionable facts. The goal is to understand what is happening right now inside the customer base—basic profiles, usage statistics, purchase frequencies, average order values, geographic spreads, and any other high-level patterns hiding in plain sight. You may work in Excel, Python (pandas, matplotlib, seaborn), R, or a BI tool such as Tableau or Power BI; choose whichever environment lets you move fastest while keeping results transparent and reproducible. Deliverables • A cleaned, well-documented version of the original customer data • A concise report (PDF or notebook) explaining methods and key descriptive findings • Clear visualisations that make the numbers easy to digest (charts, tables, dashboards) • A brief hand-off call or notes so I can repeat or extend the analysis later All insights must stem from descriptive analysis only; no forecasting or prescriptive modelling is required at this stage. If anything in the dataset looks off—missing values, outliers, inconsistent formats—kindly flag it and show how you handled it. I’m ready to supply the data immediately and would like an initial draft within a few days.