Engineering Insights

Insights

Engineering articles on data platforms, AI analytics, and the architecture decisions behind trustworthy systems.

2025-06-016 min read

Why AI Needs a Semantic Layer

LLMs can reason over data fluently. The problem is not capability — it is context. Without a semantic layer, AI analytics is a probabilistic exercise. With one, it becomes deterministic.

Semantic LayerAI AnalyticsdbtLLM

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2025-05-155 min read

Why Dashboards Fail

Most analytics investments produce dashboards. Most dashboards are underused within six months. The problem is not the tool. It is what dashboards are designed to answer.

AnalyticsDashboardsData StrategyDecision Intelligence

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2025-05-017 min read

Building Trustworthy Analytics

The most common analytics problem is not missing data. It is data nobody trusts. Trustworthiness is an architecture decision, not a QA process.

Data QualitydbtMetric GovernanceAnalytics Engineering

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2025-04-158 min read

From DWH to AI Agents

The data warehouse was built for humans. The semantic layer made it accessible. AI agents are what happens when you close the loop — from data to decision, without human intervention.

AI AgentsDWHSemantic LayerAutonomous Analytics

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