⏩ TL;DR – Read the full story on my Substack: 🔗 The Holy Trinity for Enterprise Data Foundations
Here’s the Real Bible for enterprise data foundations!
I read three exceptional books every Data & AI team must know.
I’m breaking them down in my new Substack article series – this post is the summary of the first one.
The real foundation of AI isn’t AI. It’s metadata quality, data value, and coordinated architecture. Most companies miss this. Your AI will fail if these three pillars are weak.
The Bible
These are the three books at the center of the series:
Data Quality ROI – Gaurav Patole
Clear patterns for business ownership, ROI arguments, and human alignment. It explains how to make people care about data quality so AI doesn’t amplify garbage.
Halo Data – Caroline Carruthers & Peter Jackson
A practical way to measure data value using metadata “energy”. It tells you which metadata is truly worth enriching.
Fundamentals of Metadata Management (The Meta Grid) – Ole Olesen-Bagneux
A modern approach to coordinating metadata silos instead of replacing them. It shows how to align glossaries, lineage, catalogs, and CMDBs at scale.
Together these three books offer a complete model for building AI-ready data foundations.
Why it matters now?
LLMs, semantic layers, and agentic workflows collapse when metadata is:
- inconsistent
- untrusted
- fragmented across tools
- disconnected from business ownership
Your AI cannot think straight if the metadata beneath it is confused.
What my first article of the series covers:
- How each book contributes a different piece of the puzzle
- Why AI workflows need all three perspectives
- How to combine them into a single metadata strategy
- Reading paths depending on whether you start with culture, architecture, or value
- A preview of the upcoming 10-dimension analysis series
💡 Takeaway
AI success depends on metadata discipline. Fix data quality, quantify metadata value, and coordinate your repositories. Do this well and every AI initiative becomes easier, faster, and more reliable.
👉 Read the full story on my Substack: 🔗 The Holy Trinity for Enterprise Data Foundations
My Track Record
Over nearly 30 years, I’ve been building exactly these bridges between business, processes, and data:
- At A1 Telekom Austria, I designed and implemented the Enterprise Information Architecture, later leading the development of the central Big Data Platform and Data Lake.
- I created frameworks for data ingestion, integration, and governance, replacing legacy systems with modern, scalable architectures.
- I’ve worked on data modeling, data warehouses, and BI systems that supported planning, reporting, and decision-making across the company.
- Today, I’m expanding my expertise into Machine Learning, Generative AI, and platforms like Databricks and Azure, making sure my architectural work fully enables next-generation AI solutions.
My passion has always been the same: turning data into clarity and business value.