What If AI’s Mistakes Aren’t Bugs, but Features?
We often say AI’s mistakes are “by design,” but they’re really not. AI wasn’t built to fail in these specific…
Data Education
A Practical Approach to Data Mesh Implementation
It’s easy to make the case for building a data mesh within your business. By enabling a decentralized approach to…
The Data-Centric Revolution: ABox Versioning
Have you ever invented something, seemingly out of whole cloth, only to do a simple Google search to find out…
Legal Issues for Data Professionals: A New Data Licensing Model
Setting the Stage: Data as a Business Asset This column presents a new model for licensing and sharing data, one that…
Predictive Analytics Supports Citizen Data Scientists
Like every other business, your organization must plan for success. In order to do this, the team must have a…
The Future of Data Engineering and AI-Driven Analytics in the Workforce
The future of data engineering and AI-driven analytics is both exciting and complex. As technology continues to evolve at a…
Beyond Paper Policies: Building a Living Data Policy Framework
Data policies serve as the guardrails for how organizations manage their most valuable asset: data. Just as communities establish guidelines…
AI’s Newest Employee: Who Bears the Burden of Your Digital Co-Workers?
Digital co-workers are no longer hypothetical. AI-driven agents (“Agentics”) are creeping into every function, every decision process, and every interaction…
Data Is Risky Business: Is Data Governance Failing? Or Are We Failing Data Governance?
In January, CDO Magazine carried an article by a consortium of authors including Dr. Tom Redman, John Ladley, Dr. Anne-Marie…
Through the Looking Glass: Technology Solutions in Search of a Problem
When I read about new technologies, I often think of the movie “Field of Dreams.” The protagonist builds a baseball…