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.
501 articles from this blog
Explains why policy-as-code, not RAG, is the key to secure enterprise AI by embedding authorization into query engines.
A plain English guide explaining how LLMs like ChatGPT actually work, covering prediction, vectors, embeddings, and common misconceptions.
Compares ChatGPT and Claude paid tiers, features, and practical productivity examples for choosing the best AI assistant.
A technical guide to running open-source AI models locally, covering hardware, tools like Ollama and Hermes Agent, and privacy benefits.
A detailed guide to specialized AI tools for music, video, image generation, and design, including pricing and use cases.
Explore Google's free AI tools including Gemini, NotebookLM, AI Studio, and more for daily productivity without paying.
A comprehensive overview of agentic coding tools in 2026, covering CLI agents, UI-based IDEs, autonomous agents, and model routers.
Overview of AI agent tooling from major data platforms in 2026, focusing on MCP integration and native capabilities.
Guide to securing Apache Iceberg tables with row/column-level access control using Apache Polaris and query engine policies.
Compares 2026 agentic analytics tools ThoughtSpot, Databricks, and Tableau, evaluating their AI agent capabilities for data querying and analysis.
Explains mathematically why traditional lakehouses fail AI agents and introduces the agentic lakehouse concept.
Explains the architecture of agentic analytics systems, focusing on the ReAct reasoning loop, tool access, error handling, and multi-agent setups.
Guide to Apache Iceberg v3 features including deletion vectors, new data types, encryption, and upgrade planning for production workloads.
Explores how agentic AI auto-heals and protects enterprise data pipelines by replacing static alerts with autonomous monitoring and recovery.
Tutorial on building a custom agentic analytics system using Python, LangChain, and Dremio SQL data lakes for automated SQL investigation.
Explains the 2026 unified data architecture for multi-cloud data lakehouses using open standards like Apache Iceberg.
Explores zero-ETL federation as a real-time data access method for AI agents, replacing batch ETL to enable live cross-enterprise analytics.
A guide to preventing data swamps in lakehouses through active governance, metadata stewardship, schema evolution safety, and drift detection.
Explains how Apache Iceberg enables hybrid-cloud analytics for regulated markets by separating storage, compute, and catalog.
Explores concurrency and isolation challenges when multiple AI agents query a lakehouse, using Iceberg's optimistic concurrency control and access policies.
