https://github.com/djdhairya/uber-data-analytics
Mage Vm
https://github.com/djdhairya/uber-data-analytics
aiml api bigdata bigquery deep-learning docker google-maps-api ml python3 sql ssh vmware
Last synced: about 2 months ago
JSON representation
Mage Vm
- Host: GitHub
- URL: https://github.com/djdhairya/uber-data-analytics
- Owner: djdhairya
- License: mit
- Created: 2024-01-08T17:27:01.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-01-10T20:47:39.000Z (over 2 years ago)
- Last Synced: 2025-10-10T16:24:49.175Z (8 months ago)
- Topics: aiml, api, bigdata, bigquery, deep-learning, docker, google-maps-api, ml, python3, sql, ssh, vmware
- Language: Jupyter Notebook
- Homepage: https://github.com/mage-ai/mage-ai
- Size: 4.93 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Uber-Data-Analytics
## 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
1. Google Storage
2. Compute Instance
3. BigQuery
4. Looker Studio
Modern Data Pipeine Tool - https://www.mage.ai/
Contibute to this open source project - https://github.com/mage-ai/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.
More info about dataset can be found here:
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
## Complete Video Tutorial
Video Link - https://youtu.be/WpQECq5Hx9g