Insights

Insights

Gain expert strategies, real-world perspectives, and best practices in data engineering, analytics, and AI. Explore our latest insights to stay ahead in the ever-evolving data landscape.

Blog posts

AI Access Management: Three Governance Layers

AI Governance AI Agents Data Governance Data Architecture Access Management

AI introduces a new access management challenge: what the user can see, what the agent can see, and what the LLM can see are not the same thing. This article explores how AI governance can be integrated into an existing hub-and-domain data architecture through identity groups, secured schemas, and governed AI harnesses.

Hub & Domains: A Practical Data Operating Model

Data Governance Data Mesh Data Architecture Data Strategy Data Management

Domains bring data ownership closer to the business, but governance, access management, and shared standards remain difficult to decentralize. This article explores a Hub & Domains operating model that combines business ownership with centralized governance and platform controls.

Certified Metrics: From Fact to Dashboard

Metrics Data Governance Business Intelligence Analytics

Certified metrics require more than documented formulas. Learn how facts, measures, dimensions, aggregate metrics, and dashboards work together to create trusted and reusable business metrics.

Distributing Facts and Dimensions: Governance, Access & Ownership

Data Governance Data Architecture Data Warehouse Data Modeling Business Intelligence

Building facts and dimensions is only part of the challenge. This article explores how certified data should be distributed across the organization through controlled access paths, ownership models, governance processes, and support structures.

What the Claude Code Leak Reveals About Enterprise AI

AI Strategy AI Governance Enterprise AI AI Agents Software Architecture

The Claude Code leak provides a practical look at AI architecture and where value is created in enterprise AI applications. This article explores why governance, workflows, and deterministic logic often matter more than AI itself when building reliable, cost-effective solutions.

Flat Tables vs. Snowflake Semantic Models: The Ultimate BI Data Debate

Business Intelligence Data Modeling Flat Tables Semantic Models

Structuring data for BI is a key decision that impacts performance, scalability, and data consistency. This article compares flat tables and semantic models, highlighting the strengths and trade-offs of each. Learn how a hybrid approach can offer the best of both worlds—combining consistency, flexibility, and efficient analytics across tools and teams.