Uber Data Analytics | Data Engineering GCP Project

This project uses GCP Storage, Python, Compute Instance, Mage Data Pipeline Tool, BigQuery, and Looker Studio for performing data analytics on Uber data and building a Dashboard.

Architecture

Technology Used

Programming Language: Python

Google Cloud Platform:

Google Storage
Compute Instance
BigQuery
Looker Studio

Modern Data Pipeline Tool: Mage

Dataset Used

TLC Trip Record Data includes pick-up/drop-off dates and times, locations, trip distances, fares, rate types, payment types, and passenger counts.

For more information about the dataset:

Data Model

Workflow: Mage -> GCP (BigQuery) -> Looker Studio

Dashboard