New York City Taxi and Limousine Commission Department Data Analytics

The goal of the project was to create a data engineering pipeline using the NYC TLC Rideshare data and create a final dashboard to perform the analytics.

Technologies Used:

• Python3 and Jupyter Notebook to understand and transform the data.
• Google Cloud Storage Bucket to store the data.
• Google Cloud Compute Engine integrated with Mage (A modern replacement of Apache Airflow) to build the data pipeline.
• Google Cloud BigQuery to store the database and create analytical layer.
• Google Looker Studio to build the final dashboard.

Data Model

Mage Data Pipeline

Looker Studio Dashboard

Final Dashboard : Google Looker Studio