The goal of this project is to create a Data Engineering Pipeline and a Data Analytics Dashboard on Uber Trip data using Google Cloud Platform Mage AI Tool, and Looker Studio.
Programming Languages Used - Python, SQL
Google Cloud Platform
- Google Bucket Storage
- Compute Engine Instance (for Mage AI deployment)
- BigQuery (Creating and Joining Tables for Analytics)
- Looker Studio (Analytics Dashboard)
Modern Data Pipeine Tool - https://www.mage.ai/
Contibute to this open source project - https://github.com/mage-ai/mage-ai
TLC Trip Record Data Yellow and green taxi trip records include fields capturing pick-up and drop-off dates/times, pick-up and drop-off locations, trip distances, itemized fares, rate types, payment types, and driver-reported passenger counts.
Please check the data foler for the dataset used for this project
More info about dataset can be found here:
- Website - https://www.nyc.gov/site/tlc/about/tlc-trip-record-data.page
- Data Dictionary - https://www.nyc.gov/assets/tlc/downloads/pdf/data_dictionary_trip_records_yellow.pdf
The Looker Data Analytics Dashboard created looks like the below:
The complete Data Analytics Dashboard can be viewed here: Looker Dashboard