https://github.com/tknishh/travelmeter
Performed data analytics on Uber data using various tools and technologies, including GCP Storage, Python, Compute Instance, Mage Data Pipeline Tool, BigQuery, and Looker Studio.
https://github.com/tknishh/travelmeter
data-engineering gcp mage-ai modern-project uber-data-analysis
Last synced: 3 months ago
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Performed data analytics on Uber data using various tools and technologies, including GCP Storage, Python, Compute Instance, Mage Data Pipeline Tool, BigQuery, and Looker Studio.
- Host: GitHub
- URL: https://github.com/tknishh/travelmeter
- Owner: tknishh
- Created: 2023-05-10T12:32:24.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2023-10-05T07:39:41.000Z (over 1 year ago)
- Last Synced: 2023-10-06T13:04:38.630Z (over 1 year ago)
- Topics: data-engineering, gcp, mage-ai, modern-project, uber-data-analysis
- Language: Jupyter Notebook
- Homepage:
- Size: 4.32 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# TravelMeter
## Introduction
The goal of this project is to 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.
## Architecture
## Technology Used
- Programming Language - Python
- Google Cloud Platform
- Google Storage
- Compute Instance
- BigQuery
- 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 and times, pick-up and drop-off locations, trip distances, itemized fares, rate types, payment types, and driver-reported passenger counts.
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
## Data Model
