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Explore how streaming data applications enable real-time environmental insights, driving sustainable decisions and cost savings while addressing ethical considerations and maintaining profitability.
Develop a Streamlit data app to visualize advertising ROI using Snowpark Python. Learn data ingestion, transformation, ML modeling, and interactive visualization techniques.
Discover an automated system for detecting and remediating degraded storage in Kafka, improving cluster performance and availability. Learn about monitoring, algorithm formulation, and mitigation strategies.
Implement dynamic Change Data Capture for large databases using Flink CDC connectors and consistent hashing. Overcome challenges with incremental snapshotting and Postgres replication slots.
Explore innovative incremental snapshot techniques for Debezium CDC connectors. Learn to pause, resume, and parallelize snapshots, and customize snapshot contents for efficient data pipeline management.
Explore strategies for modernizing data architecture, from technical aspects like JSON Schema and OpenTelemetry to human factors like building trust and adopting a product-focused mindset.
Explore challenges in building a streaming SQL engine like Flink SQL. Learn about late data handling, change data processing, event ordering, nondeterminism, and state storage in stream processing.
Explore NASA's use of Kafka for real-time astronomy data sharing, including architectural choices and OAuth2 implementation for public access in the General Coordinates Network.
Unlock real-time event streams to detect trends, issues, and threats. Learn how IBM Event Automation empowers teams to process events, define scenarios, and automate decisions.
Explore a novel system for microservices that handles state, communication, and consistency. Learn how it complements event-processing systems for complex control flow and coordination in distributed applications.
Explore Lyft's real-time optimization platform evolution, focusing on streaming infrastructure for marketplace balance, scalability, and decision-making using Kafka and data science tools.
Explore the serverless lakehouse architecture for real-time data streaming. Learn its benefits, implementation, and cost-saving potential through an interactive demo using live events from mobile devices.
Efficiently stream data into medallion architecture using Apache Hudi. Learn about record index, incremental updates, and CDC features to overcome challenges and build low-latency data processing systems.
Learn to create powerful data pipelines by combining Apache Kafka and InfluxDB for real-time processing, analysis, and visualization of large-scale data, especially in IoT applications.
Optimize Kafka Connect clusters for scalability. Learn best practices to configure and manage Kafka Connect effectively, ensuring successful integration of external systems with Apache Kafka at scale.
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