Netflix details how they monitor and explain ML models in payments, capturing metrics, tracing predictions, and detecting drift. Built for compliance, reliability, and scaling observability patterns into other domains.
How to handle unstructured data in enterprise environments with metadata-driven governance, scalable storage, and unified architectures that bring structured and unstructured together.
New open-source support from Aiven lets Kafka log segments convert directly to Parquet, making them usable by both Iceberg and Kafka tiered storage. A free, practical step toward true stream–table unification.
Meta introduces a multi-agent framework where query agents and owner agents collaborate to ensure secure warehouse access. Balances speed for analysts with compliance and audit guarantees.
A hands-on walkthrough for scaling log ingestion with OpenSearch Service, covering pipeline design, indexing, and best practices for reliable, high-volume observability systems.
A Python package connecting Apache Flink with the Model Context Protocol, letting AI models stream predictions and decisions into real-time pipelines.
Power BI introduces the .PBIR format to version-control and manage reports in CI/CD workflows. Streamlines metadata, collaboration, and lifecycle management for enterprise BI.
Akamai’s CTO explains why AI agents lag behind the JARVIS dream and what’s needed to close the gap. Covers edge AI, model efficiency, hybrid reasoning, and a realistic 5–7 year horizon.
Unfiltered critique of the AI startup hype cycle. From ChatGPT wrappers to déjà vu blockchain pitches, this episode calls out VCs and founders riding the wave without tech depth.
Practical strategies for reducing data engineering burnout. Learn how automation, simplified workflows, and maintainable architectures can improve both productivity and team health.
Tour of open table formats, partitioning, tiering, and compliance strategies, plus a live demo.
Databricks One gives business users a single interface for data and AI insights without coding.
A leading bank kept its mainframe as the source of truth but shifted heavy compute to Flink, cutting MIPS by 90 percent in three weeks and saving $1M annually. Architecture includes COBOL to Java refactors, Kafka, Azure Blob, and exactly–once streaming.