Comprehensive Sales Data Analysis

I will provide a full export of my sales records and need a data analyst who can dive straight into the numbers, extract meaningful patterns, and translate them into recommendations the business can act on. The dataset includes fields such as product, region, channel, units, revenue, and date; if you discover gaps or outliers along the way, feel free to flag them so we can address them together.

Your task is to explore the data statistically and visually, highlight the drivers behind revenue fluctuations, surface any seasonality or regional differences, and call out under-performing product lines. You are welcome to work in Python with pandas, NumPy, seaborn / matplotlib, or R and SQL—whatever makes the workflow efficient—as long as the final insights are presented in a clear, non-technical format my broader team can understand.

Deliverables:
• Reproducible analysis file (notebook, script, or spreadsheet)
• Concise report summarising findings, implications, and next steps (PDF or Word)
• Well-labelled charts and tables suitable for slide decks

Acceptance criteria:
• All calculations can be rerun without errors
• Narrative ties every statistic to a practical recommendation
• Visuals are clean, readable, and use consistent styling

If you have recent examples of similar sales analyses, feel free to mention them when you respond.