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Uber Data Analytics | Modern Data Engineering GCP Project

Introduction

The goal of this project is to recreate an existing data analytics project on Uber data, utilizing various tools and technologies such as GCP Storage, Python, Compute Instance, Mage Data Pipeline Tool, BigQuery, and Looker Studio.

Architecture

Example Image

Technology Used

  • Programming Language - Python

Google Cloud Platform

  1. Google Storage
  2. Compute Instance
  3. BigQuery
  4. Looker Studio

Modern Data Pipeine Tool - https://www.mage.ai/

Dataset Used

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.

I used a part of this dataset :

  1. Website - https://www.nyc.gov/site/tlc/about/tlc-trip-record-data.page
  2. Data Dictionary - https://www.nyc.gov/assets/tlc/downloads/pdf/data_dictionary_trip_records_yellow.pdf

Data Model

Example Image

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