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.
388 articles from this blog
Explains what a semantic layer is, its components, and how it provides consistent business definitions for data queries and AI agents.
Seven critical mistakes that can derail semantic layer projects in data engineering, with practical advice on how to avoid them.
Explains how a self-documenting semantic layer uses AI to automate data documentation, reducing manual work and governance risks for data teams.
Explains Headless BI and how a universal semantic layer centralizes metric definitions to replace tool-specific models, enabling consistent analytics.
Explains how data virtualization and a semantic layer enable querying distributed data without copying, reducing costs and improving freshness.
Explains how a semantic layer enforces data governance by embedding policies directly into the query path, ensuring consistent metrics and access control.
Explains why AI data analytics fail without a semantic layer to define business metrics and ensure accurate, secure queries.
Explains the distinct roles of data catalogs and semantic layers in data architecture, arguing they are complementary tools.
Explains the difference between a metrics layer and a semantic layer in data architecture, clarifying their distinct roles and relationship.
A step-by-step guide to building a robust semantic layer for consistent data metrics, covering architecture, stakeholder alignment, and implementation.
Seven common data modeling mistakes that cause reporting errors and slow analytics, with practical solutions to avoid them.
Explains Data Vault data modeling, its core components (Hubs, Links, Satellites), and the problems it solves for complex, evolving data sources.
Explains database denormalization: when to flatten data for faster analytics queries and when to avoid it.
Explains why transactional data models are inefficient for analytics and how to design denormalized, query-optimized models for better performance.
Explains Slowly Changing Dimensions (SCD) types 1-3 for managing data history in data warehouses, with practical examples.
A comprehensive guide exploring the taxonomy, tools, and best practices for using AI-assisted coding tools in modern software development.
Explains Recursive Language Models (RLMs), which are LLMs that call themselves to break complex tasks into structured, reusable steps.
A 2025 year-in-review of key Apache data projects: Iceberg, Polaris, Parquet, and Arrow, detailing their major updates and future roadmap.
Introduces DremioFrame and IceFrame, two new Python libraries for simplifying work with Dremio and Apache Iceberg tables.
Introduces dremioframe, a Python DataFrame library for querying Dremio with a pandas-like API, generating SQL under the hood.
