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Data Professional Introspective: Your Organization Can’t Create an EDM Strategy
Some countries successfully create long-term strategic plans. For example, China’s first 100-year plan was aimed at the elimination of extreme poverty by 2020. In 1980, there were 540M people living in extreme poverty; by 2014, there were only 80 million. The second 100-year plan, targeted for 2050, calls for achieving 30% of global GDP, to […]


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Author: Melanie Mecca

All in the Data: Too Soon for Q Governance?
Quantum computing, with its groundbreaking capabilities, is poised to redefine how organizations solve complex problems and innovate in ways previously unimaginable. As industries begin to explore its potential, a pressing question emerges: Are we ready to govern this new frontier? Much like the evolution of AI necessitated AI governance, quantum computing demands its own variation […]


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Author: Robert S. Seiner

The Data-Centric Revolution: Putting Knowledge Into Our Knowledge Graphs
I recently gave a presentation called “Knowledge Management and Knowledge Graphs” at a KMWorld conference, and a new picture of the relationship between knowledge management and knowledge graphs gradually came into focus. I recognized that the knowledge graph community has gotten quite good at organizing and harmonizing data and information, but there is little knowledge […]


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Author: Dave McComb

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 the years, I’ve seen a trend — more and more emphasis on AI.   I’ve taken to asking a question at these conferences: What does data quality mean for unstructured data? This is my version of […]


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Author: Randall Gordon

Data Speaks for Itself: Data Validation – Data Accuracy Imposter or Assistant?
In my last article, “The Shift from Syntactic to Semantic Data Curation and What It Means for Data Quality” published in the August 2024 issue of this newsletter, I argued how the adoption of generative AI will change the focus and scope of data quality management (DQM). Because data quality is measured in the degree […]


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Author: Dr. John Talburt

Data Leader’s Playbook for Data Mapping
I’ve been thinking a lot about data mapping lately. I know, weird, right? With analytics, AI, cloud, etc., why would someone do that? What’s even stranger is that I’ve been thinking about its impact on data leaders. For clarity’s sake, I’m not talking about geographic maps with data points, I’m referring to the process of […]


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Author: John Wills

Through the Looking Glass: More Metaphors and LLMs
Part I When I finished my last column, “Through the Looking Glass: Metaphors, MUNCH, and Large Language Models,” I stated my intention to follow up with part II. I would cover whether a knowledge graph’s vocabulary of “triples” relates to metaphoric thinking. I even considered challenging an LLM on its ability to understand metaphors to […]


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Author: Randall Gordon

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 the private sector. (This contrasts with AI use in U.S. federal agencies, as discussed below.) This absence of such a federal law contrasts with the recently enacted AU AI law.  Instead, in the U.S., there […]


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Author: William A. Tanenbaum

Data Is Risky Business: Scaling Data Governance to the National Stage
I recently started a doctorate. And because I obviously have too much free time after running my business, teaching, and writing columns for august publications like this, I’m looking at data governance. But not at the level of the organization. My doctoral research will be a deep dive into some oft-neglected human factors that need to […]


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Author: Daragh O Brien

The Data-Centric Revolution: Dealing with Data Complexity
There are many perennial issues with data: data quality, data access, data provenance, and data meaning. I will contend in this article that the central issue around which these others revolve is data complexity. It’s the complexity of data that creates and perpetuates these other problems. As we’ll see, it is a tractable problem that […]


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Author: Dave McComb

Eyes on Data: Understanding Data Products and Their Role in Data Marketplaces
In the rapidly evolving landscape of data management, the concept of data products has emerged as a cornerstone for effective data utilization and governance. Industry experts have shed light on the critical nature of data products, their distinction from data assets, and their pivotal role in data marketplaces. As organizations strive to maximize the value […]


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Author: EDM Council

A Step Ahead: IoT Sensors – Where Vast Data Comes From
The insight we gain from an IoT system is derived from the data obtained by its sensors. Driven by innovations in materials and nanotechnology, sensor technology has been developing at unprecedented speeds and has resulted in lower-cost sensors that have better accuracy, are smaller in size, and able to detect or measure the presence of […]


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Author: The MITRE Corporation

Data Professional Introspective: The Data Management Education Program (Part 2)
In my work with the EDM Council’s Data Management Capability Assessment Model (DCAM) 3.0 development group, we are adding a capability that has remained under the radar in our industry, that is, the responsibility of the Data Management Program to determine concept and knowledge gaps within its staff resources. The organization should then plan, organize, […]


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Author: Melanie Mecca

The Book Look: AI Governance
Technics Publications has started publishing a line of Data-Driven AI books, and one of the first books in this series is “AI Governance” by Dr. Darryl J Carlton. The goal of the book in one sentence is to enable the reader to gain the knowledge and tools to effectively govern and oversee the use of […]


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Author: Steve Hoberman

Through the Looking Glass: Metaphors, MUNCH, and Large Language Models
“What’s a metaphor?”  Mr. Biergel posed the question one morning to my high school grammar class. Being typical teenagers, we looked at him with blank-eyed stares. We expected that if we waited long enough, he’d write a paragraph-long definition on the blackboard.  “What’s a metaphor?” he repeated.  “A place for cows to graze!”  We groaned. […]


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Author: Randall Gordon

Legal Issues for Data Professionals: Pros and Cons of AI in Healthcare (Part 1)
The use of Artificial Intelligence (AI) in healthcare provides promises, risks, and unintended consequences. This column addresses the evolving AI issues in connection with the following topics: As used in this column, “AI” covers both generative and non-generative AI, with a focus on machine learning as part of non-generative AI. Reducing Administrative Burdens on Physicians  […]


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Author: William A. Tanenbaum

The Data-Centric Revolution: Who Doesn’t Need Data-Centric?
Several years ago, as part of some strategic marketing, we decided to target certain companies and industries. The thinking was and is, that certain sectors are inherently more amenable to the economic arguments behind the data-centric approach. We didn’t do any market research, didn’t do any surveys, didn’t purchase any reports or data, we just […]


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Author: Dave McComb

The Art of Lean Governance: What We Can Learn from HAZMAT Professionals
The collapse of the Francis Scott Key bridge on March 26, 2024, was a tragic loss of life and disruption to the shipping supply chain on a global scale that will take months, if not years, to fully recover. A major shipping artery in and out of the United States was severed, stranding ships on […]


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Author: Steve Zagoudis

Eyes on Data: Improving ESG Reporting with Established Industry Standards
In today’s rapidly evolving corporate landscape, environmental, social, and governance (ESG) reporting has become a focal point for organizations aiming to demonstrate their commitment to sustainability and responsible business practices and comply with a growing roster of regulations. As companies navigate the complexities of ESG reporting, they increasingly seek guidance on how to effectively manage […]


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Author: EDM Council

Data Professional Introspective: The Data Management Education Program
In my work with the EDM Council’s Data Management Capability Assessment Model (DCAM) 3.0 development group, we are adding a capability that has remained under the radar in our industry: the responsibility of the Data Management Program to determine concept and knowledge gaps within its staff resources. The organization should then plan, organize, and make […]


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Author: Melanie Mecca

Data Is Risky Business: The Opportunity Exists Between Keyboard and Chair
I’m doing some research work for a thing (more on that thing later in the column). My research has had me diving through all the published academic research in the field of data governance (DG) that deals with critical success factors for sustainable (as in: “not falling over and sinking into a swamp with all […]


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Author: Daragh O Brien

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