tknishh/uber-mage-data-analysis by Tanish Khandelwaltknishh/uber-mage-data-analysis by Tanish Khandelwal

tknishh/uber-mage-data-analysis

Tanish Khandelwal

Database Engineer

Data Analyst

ML Engineer

Google Cloud Platform

Looker

Python

Uber-Mage-data-Analysis

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

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Posted Sep 2, 2023

Performed data analytics on Uber data using various tools and technologies, including GCP Storage, Python, Compute Instance, Mage Data Pipeline Tool, BigQuery,…

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Database Engineer

Data Analyst

ML Engineer

Google Cloud Platform

Looker

Python

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