themihirmathur/Uber-Data-Analytics — reverse-engineered prompt

Build me an Uber trip data analytics project that takes NYC TLC trip record data, cleans it, loads it into Google Cloud, and helps me see useful ride patterns.

I want a simple end to end pipeline using Python, Google Cloud Storage, a Compute VM, Mage for the workflow, and BigQuery for the final tables. The data should be organized into sensible tables for trips, locations, fares, payments, and times so it is easy to query. Please include SQL that answers questions like busiest trip hours, most common pick up and drop off locations, average fare and distance, payment type split, and passenger count trends.

Also create a clear notebook or scripts that explain the process step by step, plus setup instructions for running it on GCP. If possible, include guidance for connecting the BigQuery results to Looker Studio and building a simple dashboard. Look up current docs online if you need to.