Through the Looking Glass: What Does Data Quality Mean for Unstructured Data?
I go to data conferences. Frequently. Almost always right here in NYC. We have lots of data conferences here. Over…
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Legal Issues for Data Professionals: Current Leading U.S. AI Laws
There is no nationwide federal law in the U.S. that specifically regulates the development, deployment, and use of AI in…
Ensuring AI-Ready Data
Being an AI-ready organization involves identifying and then overcoming data issues that hinder the effective use of AI and generative…
The Rising Importance of AI Governance
AI governance has become a critical topic in today’s technological landscape, especially with the rise of AI and GenAI. As…
Six Data Quality Dimensions to Get Your Data AI-Ready
If you look at Google Trends, you’ll see that the explosion of searches for generative AI (GenAI) and large language…
Crossing the Data Divide: AI Data Assistants — A Data Leader’s Force Multiplier
The focus of my last column, titled Crossing the Data Divide: Data Catalogs and the Generative AI Wave, was on…
Data Speaks for Itself: Is AI the Cure for Data Curation?
By now, it is clear to everyone that AI, especially generative AI, is the only topic you’re allowed to write…
Crossing the Data Divide: Data Catalogs and the Generative AI Wave
The “Tide” of LLMs Has Reached Our Shores As a career data professional and having spent most of the last…
The AI Playbook: Providing Important Reminders to Data Professionals
Eric Siegel’s “The AI Playbook” serves as a crucial guide, offering important insights for data professionals and their internal customers…
Elevating Data and Analytics for 2024: A GenAI Imperative
As GenAI ascends in priority for CIOs, CDOs, and business leaders, 2023 has placed data and analytics in the spotlight.…