Development of a Cloud-Based Big Data Platform for Automotive Data Management and Automation

The client faces challenges with manual data management, inconsistent data quality, limited scalability, and high maintenance efforts in their existing data warehouse system. They require a modern, cloud-based solution capable of processing large data volumes efficiently, ensuring data accuracy, and supporting automation of business processes.

A large automotive aftermarket data management company seeking to modernize its data platform, enhance data processing capabilities, and automate key workflows to improve efficiency and scalability.

• Design and develop a cost-efficient, scalable, and easy-to-maintain data platform based on cloud technologies.
• Establish a robust data lake infrastructure utilizing open-source frameworks to enable versioning, data replacement, and field discovery.
• Implement automation for data intake, processing, and distribution to eliminate manual interventions and improve data accuracy.
• Support high request volumes (over 200 requests per second) to facilitate complex data queries and applications.
• Enable horizontal and vertical scaling with a microservices-based architecture for future extension and flexibility.
• Develop additional modules to automate marketplace processes, such as order returns and vendor ratings, and generate comprehensive reports for end users.
• Ensure full cloud adoption leveraging managed services for data processing, storage, and orchestration.

• Data lake construction capable of aggregating and transforming large datasets from multiple sources into a unified, standardized format.
• Automated data collection, preparation, and insertion workflows using serverless cloud services.
• Implementation of a microservices-based architecture to enable scalable and modular data processing.
• Development of automation modules for processing return requests and calculating vendor ratings within a B2B marketplace environment.
• Integration with internal product data storage systems for seamless data distribution across platforms.
• Extensive API development for data accessibility and operational integration.

• Multiple data sources for raw data ingestion
• Marketplace and vendor systems for automation modules
• Internal data storage and distribution platforms

• Support for handling over 200 requests per second with complex data aggregation
• Full cloud adoption for minimized maintenance and improved performance
• Scalable architecture to support future data growth and feature expansion
• High data accuracy, consistency, and version control
• Automated testing coverage with over 767 API tests and behavior-driven automation

The deployment of the new cloud-based data platform is expected to significantly enhance data processing efficiency, reduce manual efforts, and support high-volume data requests. It aims to provide scalable, reliable, and maintainable data management capabilities that facilitate ongoing product development, automation of key business processes, and improved data accuracy, ultimately driving operational excellence and supporting strategic growth initiatives.