Sales Data Descriptive Analysis

I’m looking to hand over a set of raw sales records so you can run a thorough descriptive analysis and turn the numbers into a clear, easy-to-digest story. The work is strictly retrospective: I want to understand what has already happened, not build forecasts or optimisation models.

You’ll start by cleaning the dataset (handling missing values, standardising fields, removing obvious errors) and then generate the key metrics that reveal overall performance—totals, averages, growth rates, and any notable outliers. From there, I need intuitive visualisations—think time-series charts, category breakdowns, heat maps—that I can drop straight into a slide deck for leadership.

Preferred tools are flexible; if you’re comfortable in Excel with Power Query, Python (pandas, matplotlib, seaborn), or a BI platform like Tableau or Power BI, that works for me as long as the final visuals are polished and the underlying logic is reproducible.

Deliverables
• Cleaned, well-documented dataset (CSV or Excel)
• A concise summary report highlighting key findings (PDF or DOCX)
• Source files or notebook that walks through the analysis step-by-step
• High-resolution charts ready for presentation

I’ll supply the data as soon as we start; please outline your proposed approach and estimated timeframe so we can lock in milestones right away.