Posts

All the articles I've posted.

• 11 MIN READ•May 24, 2026

  Data Mesh After the Hype: What Actually Works

  Three years after Zhamak Dehghani's original papers, data mesh has proven valuable in specific organizational contexts and impractical in others. Here's what the practical implementations look like.

  Data Mesh Practical ImplementationData Mesh Reality CheckData Product Thinking
• 12 MIN READ•May 24, 2026

  How dbt Fusion Reshapes Analytics Engineering

  dbt Fusion entered public beta in May 2025 with a Rust-powered runtime that changes how analytics engineers develop, validate, and deploy SQL models. Here's what changed.

  Dbt Fusion Analytics EngineeringDbt Fusion RustDbt State-Aware Orchestration
• 13 MIN READ•May 24, 2026

  Using DuckDB and Polars to Query Iceberg Tables

  DuckDB 1.4 LTS and Polars streaming engine now both support reading and writing Apache Iceberg tables. Learn how to use them for lakehouse analytics in 2025.

  Duckdb Polars IcebergDuckdb Iceberg WritePolars Iceberg Sink
• 12 MIN READ•May 24, 2026

  FinOps for Data Warehouses with Open Billing Data

  The FOCUS 1.3 specification and native warehouse cost views make real-time cost attribution practical. Learn how to build a FinOps pipeline for Snowflake, BigQuery, and multi-cloud environments.

  Warehouse Finops Focus SpecificationSnowflake Cost ManagementBigquery Jobs View
• 13 MIN READ•May 24, 2026

  Designing Governed RAG on Data Products

  Enterprise RAG architecture that trusts its own data requires governance at the retrieval layer. Learn how to build governed RAG using data products, access policies, and semantic layer routing.

  Governed Rag Enterprise Data ProductsEnterprise Rag ArchitectureGoverned Retrieval Augmented Generation
• 12 MIN READ•May 24, 2026

  What Iceberg V3 Advances Mean for CDC Pipelines

  Apache Iceberg V3 brings deletion vectors and row lineage that reshape CDC pipeline design. Learn what these features mean for your streaming data architecture.

  Iceberg Cdc PipelineIceberg Deletion VectorsIceberg Row Lineage
• 13 MIN READ•May 24, 2026

  Kafka 4.0 Changes Streaming Platform Operations

  Kafka 4.0 removes ZooKeeper and ships KRaft and KIP-848 by default. Learn what those changes mean for platform operations, upgrades, and client configurations.

  Kafka 4.0 UpgradeKafka KraftZookeeper Removal Kafka
• 13 MIN READ•May 24, 2026

  Lance and Iceberg for Multimodal AI Data

  LanceDB and Apache Iceberg serve complementary roles in a multimodal AI lakehouse. Learn when to use Lance for embeddings and random access, and Iceberg for structured metadata and SQL analytics.

  Lancedb Iceberg Multimodal Ai DataLancedb FormatLance Vs Iceberg
• 13 MIN READ•May 24, 2026

  Bringing MLflow and Data Pipelines Closer Together

  MLflow 3 extends observability from classic ML experiments to GenAI tracing and data pipeline lineage. Learn how to connect data quality monitoring with model performance tracking.

  Mlflow Data Pipeline ObservabilityMlflow 3 Genai TracingMlflow Data Quality Monitoring
• 14 MIN READ•May 24, 2026

  Modern Feature Stores Beyond Batch Pipelines

  Feature stores like Feast now support streaming feature views from Kafka and Kinesis alongside batch pipelines. Learn how to build real-time features that maintain training-serving consistency.

  Feature Store Streaming Real-Time MlFeast Streaming FeaturesOnline Offline Feature Store
• 12 MIN READ•May 24, 2026

  OpenLineage as the Spine of Data Observability

  OpenLineage provides a standard API for collecting pipeline lineage across Airflow, Spark, Flink, and dbt. Learn how it powers blast radius analysis and incident triage.

  Openlineage Data ObservabilityOpenlineage AirflowOpenlineage Spark
• 12 MIN READ•May 24, 2026

  When Paimon Beats Iceberg for Mutable Streams

  Apache Paimon uses LSM-Tree storage for native CDC upserts without restart. Learn when Paimon outperforms Iceberg for high-churn mutable streaming workloads.

  Apache Paimon Mutable StreamsPaimon Vs IcebergCdc Streaming Lakehouse