I have a complete set of online and in-store sales records and want a clear, data-driven picture of which products generate the most revenue and profit across channels. Your task is to take that raw data, run a focused sales performance analysis, and deliver evidence-based insights I can act on right away. Here’s the flow I have in mind. First, you’ll clean and unify the two data sources, flagging any gaps or anomalies you notice. Next, using whichever stack you prefer—SQL, Python (pandas), Power BI, Tableau or similar—you’ll calculate key metrics such as revenue, units sold, margin, channel split and growth rate. From there, I need you to spotlight the true top sellers, call out seasonality or location effects if they exist, and surface any hidden high-potential items that deserve more promotion. Deliverables • A well-documented dataset (or reproducible query/notebook) showing all transformations • An interactive dashboard or report that lets me filter by product, date range, store vs. online, and other basic dimensions • A concise findings summary that highlights the winners, surprises, and next-step recommendations Acceptance criteria: the dashboard must refresh from the source files without manual edits, calculated totals must reconcile with my original figures, and every recommendation should tie back to a specific metric you uncovered. If this sounds like your kind of project, let me know the analytics tools you’ll use and a rough timeline for delivery.