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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 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

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

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

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

A Step Ahead: IoT Data Characteristics — Seven Vs
IoT (Internet of Things) incorporates many new and innovative technologies, such as sensors, smart devices, machine-to-machine communication, networking, advanced computing, and data analytics. One of the keys in the success of IoT is the data that flows underneath these technologies. Naturally, the IoT sensors and devices generate a huge amount of data automatically and continuously. […]


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Author: The MITRE Corporation

Data-Centric: How Big Things Get Done (in IT)
I read “How Big Things Get Done” when it first came out about six months ago.[1] I liked it then. But recently, I read another review of it, and another coin dropped. I’ll let you know what the coin was toward the end of this article, but first I need to give you my own […]


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Author: Dave McComb

The Data-Centric Revolution: Best Practices and Schools of Ontology Design
I was recently asked to present “Enterprise Ontology Design and Implementation Best Practices” to a group of motivated ontologists and wanna-be ontologists. I was flattered to be asked, but I really had to pause for a bit. First, I’m kind of jaded by the term “best practices.” Usually, it’s just a summary of what everyone […]


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Author: Dave McComb

The Data-Centric Revolution: “RDF is Too Hard”
We hear this a lot. We hear it from very smart people. Just the other day we heard someone say they had tried RDF twice at previous companies and it failed both times. (RDF stands for Resource Description Framework,[1] which is an open standard underlying many graph databases). It’s hard to convince someone like that […]


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Author: Dave McComb

Eyes on Data: An Approach to Measure Data ROI
Justifying any significant business investment is challenging. For data managers, the struggle is especially familiar. The difficulty is convincing decision makers to invest in data when measures of data’s value either do not exist or feel too ambiguous to estimate. As digital transformation accelerates, interest in frameworks for linking data to monetary measures grows.Connecting data […]


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Author: EDM Council

A Step Ahead: Data Fabric and Data Mesh – Similarities and Differences
The terms Data Mesh and Data Fabric have been used extensively as data management solutions in conversations these days, and sometimes interchangeably, to describe techniques for organizations to manage and add value to their data. In this article, we intend to clarify these terms and explain the overlaps and differences to enable the readers to […]


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Author: The MITRE Corporation

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