
Explore real-time stream processing applications with Apache Kafka co-creator Neha Narkhede. Learn how to harness continuously changing data for modern businesses and analytical processes.

Explore strategies for transforming big data into actionable insights, focusing on user-friendly tools and frameworks to empower business users in data analysis and decision-making.

Explore Spotify's Hadoop journey, from office closet to massive cluster, through failures and lessons learned. Gain insights on data infrastructure evolution and overcoming obstacles in large-scale systems.

Explore Hadoop's real-world applications for big data analysis, including social media insights and medical data processing. Learn about advanced analytics, near real-time processing, and architectural considerations.

Exploring the connection between activism and Open Data, proposing Open Analytics to transform data into actionable knowledge for social activists.

Explore Apache Pulsar for event streaming and Apache Pinot for real-time analytics. Learn how these powerful open-source tools combine to deliver scalable, low-latency data processing and analysis in cloud-native environments.

Explore serverless integration using Camel Quarkus to simplify application connectivity, leverage fast startup times, and optimize resource usage through technologies like Knative and Kafka.

Explore efficient deepfake detection using limited resources. Learn about neural networks, GANs, and practical techniques to identify AI-generated faces with high accuracy.

Explore real-time analytics optimization using Apache Kafka and Pinot. Learn how these powerful tools work together to deliver scalable, low-latency solutions for user-facing applications.

Explore the Strangler Fig Pattern for modernizing legacy systems using Change Data Capture, connectors, and stream processing techniques.

Explore strategies for implementing data quality at scale, covering challenges, metrics, and platform approaches for ensuring high-quality data in modern enterprises.

Explore the impact of machine learning, big data, and automation on our planet's future, gaining historical perspective to address key challenges in this digital revolution.

Explore Kafka Connect's power in integrating data systems, from basics to advanced techniques for efficient and scalable data pipelines.

Explore event streaming with Kafka Streams, Spring Kafka, and Actuator. Learn to build scalable, fault-tolerant applications using live coding examples for consumers, producers, and fraud detection streams.

Explore Google Dataflow's unified batch and stream processing model through real-time demonstrations, practical insights, and visualization techniques for managing data streams.

Explore real-time video analytics for football games using Apache Beam, machine learning, and cloud technologies to detect events, track players and ball, and perform game analytics.

Explore open-source technologies for flexible data pipelines, from Apache Kafka to BigQuery, with easy component swapping and cloud deployment options.

Explore Kusto for interactive Big Data analytics on Azure. Learn advanced querying, monitoring, and debugging techniques used at DocuSign through practical examples and demonstrations.

Strategies for building resilient Java Enterprise applications in production, covering circuit breakers, bulkheads, backpressure, and telemetry using MicroProfile and service meshes.

Discover Quarkus: Java's answer to nimble cloud-native technologies. Experience supersonic, subatomic Java that makes frameworks like Hibernate and Apache Camel faster, smaller, and more scalable than ever before.

Learn to implement fast, efficient stream processing with a distributed in-memory cache using Java. Discover techniques for analyzing in-memory data and integrating external data sources for high-performance analytics.