Overview
An existing ride-hailing client of Rokkun aimed to revolutionise the ride-hailing industry by leveraging data science, predictive analytics, and a robust data warehouse to create an intuitive, efficient, and secure transportation platform. They partnered with Rokkun, a machine learning development company to enhance their capabilities in these areas.
The Challenge
The client faced several challenges:
Handling massive datasets generated by ride transactions and user interactions.
Need for real-time predictive analytics for optimising ride dispatching and pricing strategies.
Requirement for a robust data warehousing solution to manage and analyse data efficiently.
Ensuring data security and privacy while operating on a large scale.
Solution
Our approach integrated several technologies and platforms:
Data Science for Demand Prediction: Utilizing Google Cloud Platform’s AI and machine learning capabilities, specifically TensorFlow, we developed predictive models that analyzed historical ride data and user patterns to forecast demand.
Data Warehousing with BigQuery: We leveraged Google BigQuery as a fully-managed data warehouse to process and query large datasets quickly, enabling real-time insights into ride dynamics and operational efficiency.
Big Data Processing with Google Cloud Dataflow: To efficiently handle the vast datasets, we decided to hire data engineers skilled in Google Cloud Dataflow for stream and batch data processing. This allowed for seamless data ingestion and transformation, preparing it for analysis and machine learning.
Predictive Analytics with AI Platform: Google Cloud AI Platform was used to deploy machine learning models that provided predictive analytics to anticipate call volumes and user behavior, enhancing decision-making for ride placement and pricing strategies.
Secure and Scalable Infrastructure: The entire solution was built on Google Cloud Platform, ensuring a secure, scalable, and resilient cloud infrastructure that could adapt to the company’s growing data needs.
Results
The deployment of the data-driven ride-hailing platform led to measurable outcomes:
Predictive models achieved an 85% accuracy rate in forecasting demand, enabling better ride availability and reduced wait times.
With BigQuery, the client processed queries 70% faster, leading to quicker insights and decision-making.
The cloud-native approach allowed the platform to effortlessly scale during peak demand, supporting a 100% increase in ride volume within the first quarter post-implementation.
Leveraging Google Cloud’s secure infrastructure, the platform maintained a flawless record of data security, with no incidents reported.
Scope of work
Data Warehouse
Data Analytics
Artificial Intelligence
Machine Learning
Cloud & DevOps
