Customer Purchase Analytics Dashboard

I’m putting together an end-to-end workflow that takes raw purchase data, cleans and structures it in SQL/Python, and then surfaces the insights in Power BI. The key business questions I need answered first are order frequency and average basket size, so those metrics must be front-and-center in the final report. You’ll start from a CSV extract that I will supply once we kick off. Expect typical ecommerce fields such as order_id, customer_id, sku, quantity, price, and timestamp, but I’m happy to adjust the pipeline if you find anything missing once you inspect the sample file. The volume is moderate for now—well under classic “big data” thresholds—so desktop-level tooling is fine. Because this is primarily strategic reporting, presentation quality matters as much as the calculation logic. Think clean DAX measures, intuitive slicers for time ranges, and visuals that an exec can grasp in seconds. Deliverables I need to sign off: • Reproducible data-prep script (SQL or Python) that loads the CSV, performs all transformations, and outputs a model ready for Power BI • A .pbix file with clearly labeled tables, measures for order frequency and basket size, and at least one dashboard page laid out for desktop and mobile views • Short README or inline comments so I can refresh the data without additional help If you have prior examples of retail analytics in Power BI, feel free to point me to them when you reply.

Project ID: 40405548