Use Cases

Optimize Ridesharing Platform

Streaming Data Lakehouse

IoT Data Streaming to Data Lakehouse help our client powers real-time analytical model, enabling more sophisticated and responsive ridesharing algorithm

Real-Time Data Engineering

Building a Streaming Pipeline

The location of each vehicle in the fleets is extremely crucial for the operation and optimization. Real-time Data Lakehouse enables our client to capture their streaming data for real-time analysis.

Real-Time Analysis

Immediate Operational Insights

Real-time analysis brings tremendous value to the operation, allowing decision and response to be made with better precision and speed. This significantly improve customers experience and accuracy of their ridesharing experiences.

Real-Time Forecast

Anticipate Changes

Real-time analysis and feature engineering subsequently enable real-time forecast, which makes it possible to anticipate changes and strategically prepare and deploy their fleet, ensuring optimal operations for an enhanced ride experiences for customers.


Better Experiences,
Improved Revenue

By enabling real-time capability, our client is now empowered with enhanced capabilities to optimize their ridesharing experiences, enabling them to refine operations and, consequently, boost their revenue.

The real-time aspects of data analytics positioned our client for future success in an ever-evolving landscape. The ridesharing platform’s ability to adapt to changing conditions, make informed decisions on the fly, and consistently deliver exceptional service for their customers.