I have a raw sales-and-revenue dataset that needs to become a set of clear, decision-ready reports as quickly as possible. The work starts with cleaning and preprocessing the data, moves through exploratory analysis, and finishes with polished visual outputs and a repeatable reporting workflow. Here’s what I need: • a fully documented Python notebook (Pandas, NumPy, Matplotlib or Seaborn, plus any Scikit-learn steps you deem valuable) that cleans the data and surfaces key metrics • concise SQL queries to reproduce the core figures directly in our database • a dashboard—Tableau, Power BI, or a Plotly-Dash web app—that lets managers slice revenue by product, region, and time period • a lightweight automation script so the report refreshes itself whenever new sales files drop Speed matters: I’d like an initial draft of the cleaned dataset and headline numbers within the first few days, with the final dashboard and automation delivered shortly after. Include sample visual screenshots or links to past work with sales data if you can. Acceptance is straightforward: the numbers must reconcile with our source sheets, the dashboard must update from a fresh CSV without manual tweaks, and all code should run end-to-end on a clean environment. If this aligns with your skill set, let’s get started right away.