Is Traditional Data Architecture Dying?
A deep, architectural walkthrough of what actually breaks β and what replaces it β in the GenAI era
Expert insights on data management, architecture, and governance from the field
A deep, architectural walkthrough of what actually breaks β and what replaces it β in the GenAI era
Why I'm spending the next 10+ weeks relearning my job β and why you might want to follow along
Why this series exists β and why now. A 10+ week journey exploring the architectural shift happening between data and AI.
Data governance isn't just a compliance checkbox. It's a shared culture where every team member owns the quality, security, and purpose of data.
Transparency isnβt just about compliance β itβs about building trust, loyalty, and competitive edge in a data-driven world.
Ethics is not a patch for when things break. It is a principle that should shape every data decision from day one.
The DAMA Wheel is not just a reference model. It's a blueprint for sustainable, enterprise-wide data maturity. Learn how to use it.
Why skipping data foundations leads to AI failure. A structured guide to climbing the data maturity pyramid.
Poor data quality is a silent killer β it erodes trust, inflates costs, and can derail entire business initiatives. Learn the 1-10-100 rule.
Have you ever opened a data lake and thought: 'I have no idea what half these files are'? Here's how metadata can save your sanity.
Data Architecture is more than storage diagrams or ERDsβit's the bridge between raw data and business value.
Data Governance isn't red tape. It's the foundation for trusted data.
Data Management is not one team's job. It's a federation of connected capabilities.
Data Management isn't a single activity. It's a coordinated effort across people, tools, processes, and policies.