Power Bi Pro Studio
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Updated
Sep 15, 2026
Power Bi Pro Studio
The goal of this project is to track the expenses of Uber Rides and Uber Eats through data Engineering processes using technologies such as Apache Airflow, AWS Redshift and Power BI.
A predictive model to help Uber drivers make more money
Analysis of Uber Data from NYC Open Data website
Uber web interface crawler / scraper - Convert the trips table into a CSV file
Exploratory and predictive data analysis with Uber's speeds dataset for London city.
Machine Learning Key Projects
EDA and data visualisation
Uber Data Analysis and Visualization using Python
This is the final data science project for USIT5609 MScIT Part II. Primarily made to learn Data Analytics, Machine Learning, and AI. To predict uber prices with external factors such as rain, temperature, time of day, day of the year, and more.
Code for fetching, sampling, and analysis of NYC taxi data from TLC and Uber for 2009-2018
This app is integrated with UBER API. You can use uber features from your app.
Addressing some data science related issuesof a ride sharing app, Pathao
This project analyzes Uber trip data using Power BI to identify trends and patterns in ride demand. Data cleaning and transformation were performed using Power Query, and an interactive dashboard was developed to visualize key insights such as peak hours and location-based trip distribution.
Operations/demand analytics on 150K Uber ride bookings — hourly demand patterns, cancellation-rate diagnostics, and ops recommendations using Python (pandas, matplotlib)
Uber and lyft data visualization, comparision and many analysis with python
A machine learning project which predicts Uber trip data for different factors.
To associate your repository with the uber-data topic, visit your repo's landing page and select "manage topics."