
Build a fully-fledged MLOps platform for small companies using open-source tools. Learn about common problems, popular tools, recent OSS projects, and a realistic roadmap for improving data and ML maturity.

Explore hybrid approaches like Lambda and Kappa architectures for combining batch and real-time systems. Learn about SaaS platforms and managed services that simplify implementation of these powerful data technologies.

Learn to build an ML experimentation platform using lakeFS for version control and reproducibility. Explore creating frameworks, reproducing iterations, and building intuitive infrastructure with open-source tools.

Explore Uber's journey in scaling their metric system, transitioning from Elasticsearch to Apache Pinot for improved reliability and performance in real-time data processing.

Gain insights from DJ Patil's decade of experience in data science, from startups to the White House. Learn key lessons and reflections on the evolving field's successes and challenges.

Explore dbt's manifest.json file, its production, and applications in data pipelines. Learn about deployment configurations, quality enforcement, and streamlined development workflows using real-world examples.

Explore DuckDB's potential to revolutionize data analytics, shifting from centralized warehouses to powerful local processing. Learn how this approach can enhance efficiency and user control in data management.

Explore Apache Flink's capabilities as a data integration hub, focusing on its SQL engine for changelog processing, CDC data handling, and materialized view maintenance. Learn about data source semantics and system integrations.

Explore the foundational choices and trade-offs in building a streaming database with Frank McSherry, Chief Scientist at Materialize. Learn manageable approaches to this complex task.

Explore Arrow Database Connectivity (ADBC), a new Apache Arrow subproject for Arrow-based database access. Learn its goals, use cases, and communication with data APIs using Arrow-native in-memory data.

Explore change data capture with Debezium and Apache Flink for microservices. Learn outbox pattern, strangler fig pattern, and saga orchestration for reliable data exchange and long-running transactions.

Explore the journey of building open-source data standards, from Apache Parquet to Arrow to OpenLineage. Gain insights into successful project ideation, growth, and ecosystem impact in data management.

Explore investor perspectives on data, AI, and ML from top venture firms. Gain insights into investment trends, criteria for early-stage teams, and future opportunities in the data infrastructure landscape.

Explore data challenges in League of Legends, including model deployment, ML stack evolution, player-facing ML, and decision science at scale for improved gaming experiences.

Explore innovative approaches to data interaction, focusing on visual, spatial, and fluid interfaces for faster decision-making. Learn about Hunch's journey in reimagining data engagement for analysts and business users.

Demystify the transition from batch to real-time processing. Learn arguments, architectures, pitfalls, and open-source tools for stream processing without overhauling your team.

Explore the powerful role of generative AI in search, focusing on NLP and Vision. Discover key challenges and promising directions through anecdotes and organizing principles.

Explore parallels between data science and model railroading, uncovering valuable insights for building real-world models and improving data science practices.

Explore Apache Calcite's SQL extensions for metrics, measures, and analytic expressions. Learn to define data models, use them in queries, and perform cross-dimensional calculations for advanced analytics.

Explore real-time schema discovery in high-volume distributed systems. Learn about schema versioning, conflict detection, compatibility, and normalization without batching processes.

Explore declarative, asset-oriented orchestration in data pipelines. Learn how this approach simplifies tasks, ensures data integrity, and implements Data Mesh as a living asset graph.