https://github.com/shubhammohanty680/uber_data_analysis
https://github.com/shubhammohanty680/uber_data_analysis
bigquery data-analysis gcp-compute gcp-project looker-studio mageai python
Last synced: 4 months ago
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- Host: GitHub
- URL: https://github.com/shubhammohanty680/uber_data_analysis
- Owner: ShubhamMohanty680
- Created: 2024-06-20T08:21:35.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-06-20T08:35:17.000Z (almost 2 years ago)
- Last Synced: 2025-03-15T07:12:15.978Z (over 1 year ago)
- Topics: bigquery, data-analysis, gcp-compute, gcp-project, looker-studio, mageai, python
- Language: Python
- Homepage:
- Size: 3.99 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Uber Data Analytics | Modern Data Engineering GCP Project
## 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.
Here is the dataset used in the video - https://github.com/darshilparmar/uber-etl-pipeline-data-engineering-project/blob/main/data/uber_data.csv
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
