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Discover how SDF's multi-dialect SQL compiler technology normalizes proprietary SQL dialects into unified logical plans, now powering dbt after acquisition, enabling improved data governance and cost optimization for cross-engine workflows.
Explore the evolution of database concurrency from traditional locking to modern scheduling approaches in distributed systems, with practical insights for building high-throughput systems where classic methods fall short.
Explore the evolution of big data ecosystems into composable architectures with open source standards like Parquet, Arrow, and Iceberg, offering guidance on avoiding vendor lock-in for data system architects and query engine builders.
Discover how InfluxDB 3 Core reimagines time series databases through a Rust rewrite using Apache Arrow, DataFusion, and Parquet, creating a diskless architecture with object storage and embedded Python capabilities.
Explore how open-source technologies and data lake standards offer alternatives to proprietary cloud data warehouses, with insights on using ClickHouse and Iceberg for flexible, cost-effective data workflows.
Explore how AI agents transform database interactions from structured queries to natural language conversations, enabling communication with data as if it were a co-worker.
Explore how embedding DuckDB into PostgreSQL creates a unified platform for both OLTP and OLAP workloads, combining transactional and analytical database capabilities for modern data platforms.
Explore the evolving database landscape with Franck Pachot as he compares PostgreSQL and MongoDB, offering practical insights on developer experience, performance, and choosing the right database for modern applications.
Discover practical applications of LLMs in data science with Hadley Wickham as he explores three key areas: writing code, writing prose, and rectangling non-rectangular data for transforming unstructured information.
Explore systematic approaches to evaluating LLM performance with practical frameworks for transforming experimental models into production-ready systems, identifying failure patterns, and establishing reliable environments.
Explore how to design reproducible data workloads over Data Lakes by decoupling code, compute, and data management for deterministic pipeline reproduction using Iceberg, Arrow, and Docker.
Discover how Uber built an end-to-end continuous experiment monitoring platform that overcomes "peeking" problems and detects performance issues across thousands of A/B tests using anytime-valid inference techniques.
Explore causal inference methods that connect A/B test results to business decisions, with insights from Roblox on attributing growth to product launches and generalizing experiment results to broader business impacts.
Discover effective statistical and technical best practices for B2B A/B testing at scale, exploring unique challenges and solutions for enterprise experimentation that differs from traditional B2C approaches.
Discover Pixeltable, an open-source infrastructure for multimodal AI workloads with a declarative, incremental approach. Learn from Apache Impala's founder how to unify data, computation, and models to simplify AI data complexity.
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