
Discover how Apache Ozone revolutionizes distributed object storage, offering scalable solutions for managing massive data volumes while ensuring reliability, cost-effectiveness, and seamless integration with Hadoop ecosystem.

Discover how to optimize data lake performance and reduce costs using open-source caching frameworks, with practical techniques for query acceleration and storage efficiency.

Discover how to build efficient medallion architecture using Apache Hudi's CDC feature and DBT for incremental data processing, enabling low-latency analytics and streamlined data transformation workflows.

Explore the architecture of modern data stacks, from warehousing to streaming solutions, while understanding the potential and limitations of open-source tools in today's data infrastructure.

Explore real-time analytics systems classification, characteristics, and technology choices for implementing different analytical solutions in production environments.

Dive into Proton's unified streaming analytics engine, exploring watermarking, query management, and real-time data processing capabilities for enhanced historical and live data analysis.

Master real-time data processing with Apache Flink, from implementing counters and windowed analytics to data enrichment techniques for high-demand distributed systems.

Discover how to build real-time GenAI pipelines by combining RisingWave's stream processing with Astra's vector embedding and similarity search capabilities for ChatGPT applications.

Discover how Prestissimo revolutionizes Presto SQL engine with C++ runtime, delivering enhanced performance, efficient memory management, and improved CPU utilization through vectorization and runtime optimizations.

Discover how AirMettle's Real-Time Smart Data Lake revolutionizes big data analytics, offering up to 100x faster processing through innovative semi-structured data handling and computational storage integration.

Explore real-world applications and challenges of Computational Storage deployment, examining efficiency gains, TCO benefits, and practical implementation strategies across various use cases.

Discover strategies for building efficient real-time data science systems. Learn about data movement, design patterns, and best practices for writing, testing, and reproducing analytics in real-time environments.

Explore real-time analytics and machine learning with HTAP databases. Learn to leverage SQL for model building and discover tools for efficient data infrastructure in this hands-on webinar.

Explore real-time streaming data processing using Ibis, Substrait, and Apache Arrow. Learn how this software stack enhances featurization workflows for fast, accurate insights and decision-making in data science.

Learn to build robust data pipelines using dbt, Airflow, and Great Expectations. Discover how these tools complement each other to ensure data quality, perform transformations, and orchestrate workflows effectively.

Explore real-time analytics for financial activities using Apache Flink. Learn about Capital One's approach to processing customer data, event-time processing, and applications in fraud detection.

Explore architectures of large-scale data analysis systems, their capabilities, and trade-offs. Learn to evaluate and choose the right system for your specific data analysis needs.

Explore state-of-the-art NLP techniques using Apache Spark, covering core algorithms, distributed pipelines, and performance optimizations for large-scale language understanding applications.

Explore the evolution from Big Data to Data Science with Usama Fayyad, focusing on predictive analytics in a changing data landscape and its impact on business growth and competitive advantage.

Explore Tachyon, a memory-centric distributed storage system for fast big data processing. Learn about its benefits, use cases, and integration with popular frameworks like Spark and Hadoop.

Explore real-time graph analytics with Raphtory, covering social networks, time-based graphs, and advanced features like historical properties and query languages.