I will provide a collection of CSV and Excel files that capture customer orders, demographics, and interaction history. I need a thorough descriptive analysis that turns these raw tables into clear insights about how my customers behave, purchase, and engage with our business. The work begins with cleaning and merging the files so every record lines up correctly—no duplicates, missing headers, or mismatched formats. From there, I want you to surface core metrics such as purchase frequency, average order value, churn/retention indicators, and segment-level patterns (new vs. repeat buyers, high vs. low spenders, and any other trends that stand out). Use whichever tools you are most comfortable with—Excel pivot tables, Python (pandas, matplotlib / seaborn), or a lightweight Power BI / Tableau dashboard—as long as the results are reproducible and easy for a non-technical audience to follow. Deliverables • A cleaned, consolidated workbook or CSV ready for future analyses • A concise report (PDF or slide deck) describing your findings, supported by clear charts and tables • The working files or scripts that generated the results so I can rerun or extend the analysis later I’m happy to answer questions about data structure or business context as you dig in, and I’ll provide prompt feedback so we can iterate quickly.