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Data Speaks for Itself: Is Your Data Quality Management Practice Ready for AI?
While everyone is asking if their data is ready for AI, I want to ask a somewhat different question: Is your data quality management (DQM)…
A Step Ahead: From Acts to Aggregates — Record-ness and Data-ness in Practice
Introduction What is the difference between records and data? What differentiates records managers from data managers? Do these…
All in the Data: Where Good Data Comes From
Let’s start with a truth that too many people still overlook — not all data is good data. Just because something is sitting in a database…
The Book Look: Rewiring Your Mind for AI
I collect baseball and non-sport cards. I started collecting when I was a kid, stopped for about 40 years, and returned to collecting again,…
Blogs
Why Data Governance Still Matters in the Age of AI
At a recent conference, I witnessed something that’s become far too common in data leadership circles: genuine surprise that chief data…
AI and Data Engineering: The Importance of Validation in Complex Data Systems
In today’s digital systems, vast volumes of information are produced daily. However, simply collecting large amounts of data is not…
What Is AI Anomia and Why Does It Matter?
We live in an age where the words we use for artificial intelligence are shaping the future faster than the technologies themselves. We…
Thoughts on the DAMA DMBoK
Many years ago, I contributed material on Database Development and Database Operations Management to the first edition of DAMA…