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Reliable Data Flows and Scalable Platforms: Tackling Key Data Challenges
Matthias Niehoff discusses bridging the gap between application and data engineering. Learn to apply software engineering best practices, embrace boring technologies, and simplify architecture.
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Achieving Precision in AI: Retrieving the Right Data Using AI Agents
Adi Polak discusses achieving precision in GenAI by moving beyond RAG to Agentic RAG. She details agent patterns, feedback loops, and using data streaming architectures to scale real-time AI.
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The Data Backbone of LLM Systems
Paul Iusztin discusses the evolution of AI engineering, highlighting the shift from model training to foundational models. He shares insights on scalable LLM systems and optimizing RAG.
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Efficient Incremental Processing with Netflix Maestro and Apache Iceberg
Jun He discusses how to use an IPS to build more reliable, efficient, and scalable data pipelines, unlocking new data processing patterns.
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1BRC–Nerd Sniping the Java Community
Gunnar Morling discusses some of the tricks employed by the fastest solutions for processing a 13 GB input file within less than two seconds through parallelization and efficient memory access.
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Architecting for Data Products
Danilo Sato discusses what constitutes a data product and different types of data products, how data products support data architecture at different levels, skills and team topologies needed.
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Incremental Data Processing with Apache Hudi
The presenters discuss an introduction to incremental data processing, contrasting it with the two prevalent processing models of today - batch and stream data processing.
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Understanding Architectures for Multi-Region Data Residency
Alex Strachan discusses challenges to build multi-region data storages, understanding why and when a business needs to do this, who are the real stakeholders, and who owns what.
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Multi-Region Data Streaming with Redpanda
Michał Maślanka introduces the design of Redpanda’s Multi-Region feature, and describes how they leveraged Raft’s properties, a constraint solver, automatic data balancing, and tiered storage.
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Graph Learning at the Scale of Modern Data Warehouses
Subramanya Dulloor outlines an approach to addressing the challenges of warehouses and shows how to build an efficient and scalable end-to-end system for graph learning in data warehouses.
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How Netflix Ensures Highly-Reliable Online Stateful Systems
Joseph Lynch discusses the architecture of Netflix's stateful caches and databases, including how they capacity plan, bulkhead, and deploy software to their global, full-active, data topology.
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Ephemeral Execution is the Future of Computing, but What about the Data?
Jerop Kipruto and Christie Warwick use Tekton to explore challenges of data gravity in ephemeral execution, discussing clean container injection mechanisms and a secure server interface.
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