Matti Georgi developed a scalable end-to-end event processing platform for the cross-media-measurement repository, focusing on efficient data ingestion, processing, and integration with analytics systems. Leveraging Kotlin, Java, and GCP, Matti designed core data models, batch readers, and parallel pipelines to optimize throughput and reduce processing time. He implemented a parallel in-memory VidIndexMap using FastUtil, enabling multi-threaded processing of large datasets and refactored existing logic for compatibility and maintainability. His work included cloud automation with Terraform and secure private networking, resulting in a robust, maintainable backend that improved performance, scalability, and security for measurement and analytics workloads.
October 2025: Focused on performance and scalability in cross-media-measurement. Delivered a parallel in-memory VidIndexMap with FastUtil, enabling multi-threaded data processing for large datasets. Refactored VidIndexMap to support parallel paths while keeping compatibility. No major bugs fixed this month; emphasis on resilience and maintainability. Business impact: faster processing, improved scalability for measurement workloads and smoother analytics integration. Technologies: Java, multi-threading, FastUtil, dependency management, code refactor.
October 2025: Focused on performance and scalability in cross-media-measurement. Delivered a parallel in-memory VidIndexMap with FastUtil, enabling multi-threaded data processing for large datasets. Refactored VidIndexMap to support parallel paths while keeping compatibility. No major bugs fixed this month; emphasis on resilience and maintainability. Business impact: faster processing, improved scalability for measurement workloads and smoother analytics integration. Technologies: Java, multi-threading, FastUtil, dependency management, code refactor.
September 2025 focused on delivering a robust, scalable end-to-end event processing platform in the cross-media measurement repo, with emphasis on core data models, batch processing, scalable pipelines, performance optimizations, and cloud automation. The work enabled more efficient ingestion, processing, and integration with downstream analytics, while laying a foundation for security and automation in cloud infrastructure.
September 2025 focused on delivering a robust, scalable end-to-end event processing platform in the cross-media measurement repo, with emphasis on core data models, batch processing, scalable pipelines, performance optimizations, and cloud automation. The work enabled more efficient ingestion, processing, and integration with downstream analytics, while laying a foundation for security and automation in cloud infrastructure.
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