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The goal of this project is to build an end to end data pipeline & perform data analytics on Uber data using various tools and technologies, including GCP Storage, Python, Compute Instance, Mage Data Pipeline Tool, BigQuery, and Looker Studio.

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claydoers/uber-modern-data-analytics-project

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Uber Data Analytics | Modern Data Engineering GCP Project

Overview

The goal of this project is to build an end to end data pipeline & perform data analytics on Uber data using various tools and technologies, including GCP Storage, Python, Compute Instance, Mage Data Pipeline Tool, BigQuery, and Looker Studio.

Technology

  • Python
  • Google Cloud Platform
  • Looker Studio
  • BigQuery
  • Compute Instance
  • Mage (Modern Data Pipeline Tool)
  • Architecture

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    Dataset

    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.

    https://www.nyc.gov/site/tlc/about/tlc-trip-record-data.page

    https://www.nyc.gov/assets/tlc/downloads/pdf/data_dictionary_trip_records_yellow.pdf

    Data Model

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    Dashboard Examples

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    About

    The goal of this project is to build an end to end data pipeline & perform data analytics on Uber data using various tools and technologies, including GCP Storage, Python, Compute Instance, Mage Data Pipeline Tool, BigQuery, and Looker Studio.

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