Alex Merced — Developer and technical writer sharing in-depth insights on data engineering, Apache Iceberg, data lakehouse architectures, Python tooling, and modern analytics platforms, with a strong focus on practical, hands-on learning.
610 articles from this blog
Analysis of Snowflake interoperable lakehouse lessons focusing on production contracts, multi-engine access, and agentic analytics challenges.
Compares Unity AI Gateway and Apache Polaris for enterprise governance, focusing on gateway vs catalog control in lakehouse architectures.
Explains how AI-ready metadata prevents query failures by making ownership, freshness, lineage, quality, and policy visible at execution time for LLM-driven analytics.
Explores autonomous materialization for agentic analytics, focusing on performance, governance, and lifecycle management in data platforms.
Explores the Dremio Agentic Lakehouse concept: data built for AI agents and platform management automated by agents, with architecture patterns and production considerations.
Explores using ClickHouse for low-latency analytical loops in active agent systems, emphasizing validation, safety, and architecture patterns.
Explains why AI agents need a context layer with lineage, quality, freshness, and ownership for reliable analytics.
Explores how lakehouses serve as an operating layer for agentic AI, focusing on governed data access, cost controls, and production reliability.
Explains why composable semantic layers are essential for AI agents to perform reliable multi-step analytical queries in production.
Explains why policy-as-code, not RAG, is the key to secure enterprise AI by embedding authorization into query engines.
Explains the four-layer architecture of an agentic lakehouse for reliable AI agent data access.
Explores concurrency and isolation challenges when AI agents write to Apache Iceberg lakehouses, covering OCC mechanics, failure modes, and architectural patterns.
Explores context layers bridging table formats and business meaning using Atlan, Iceberg v3, and Snowflake Horizon for AI agents.
Explores how ClickHouse powers real-time analytics for AI agents, with ingestion patterns, event loop architecture, and production use cases.
Explains why composable analytics outperforms metric catalogs for AI agents, enabling dynamic metric composition and deeper data reasoning.
Architecture of goal-directed analytics agents using Apache Iceberg for durable state and dynamic task decomposition.
Explains Iceberg remote signing for regulated datasets, enhancing security by issuing per-file, one-time-use pre-signed URLs instead of storage credentials.
Explains Apache Iceberg v3 deletion vectors on Snowflake, their performance benefits over v2, and implementation details.
A guide to Apache Iceberg View Federation for portable SQL views across multiple query engines in a data lakehouse.
Explains how Apache Iceberg v3 row lineage enables native CDC without external tools like Debezium or Kafka.
