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Explore how to build robust, scalable real-time data processing pipelines for capital markets in this 29-minute conference talk. Learn to construct systems that ingest, analyze, and process market data instantaneously using SQL-based analytics, enabling informed decision-making, anomaly detection, and high-frequency trading. Discover key concepts including low-latency event distribution, continuous analytics on live stock prices, and detection of trends like price anomalies and volume-weighted averages. Master the implementation of feedback loops that send processed insights back to trading systems for immediate execution, ensuring rapid response times in dynamic market conditions. Gain practical knowledge of designing real-time analytics architectures using tools like Solace for event distribution and RisingWave for streaming analytics, with coverage of scalability considerations, Change Data Capture integration, and support for various data sources including Kafka, Pulsar, and transactional databases. Understand real-world applications in portfolio monitoring, compliance, and automated trading strategies while exploring future directions toward streaming lake house architectures with native Iceberg table engine support.
