As a word, “semantics” was first used by Michel Bréal, a French philologist (a language historian),in 1883. He studied how languages are organized, how languages change as time passes, and the connections within languages. Gen erally speaking, semantics is the study of language and its meaning. More specifically, semantics can be used to describe how […]
2023: Mitigating Data Debt by Knowing or by Guessing?
One of the newer data buzzwords is “data debt.” Actually, it is approximately 10 years old, and it became popular ever since agile people realized that postponing things creates not only technical debt, but certainly also data debt. Will we, in 2023, be better at not creating so much data debt, and will it be […]
2021: Three Game-Changing Data Modeling Perspectives
Click to learn more about author Thomas Frisendal. Common wisdom has it that we humans can only focus on three things at a time. So, I had to cut down my January 2021 list of things of importance in Data Modeling in this new, fine year (I hope)! Looking at them from above, as we […]
Generally Accepted Data Modeling Principles
What can data modelers learn from accountants? Accounting is a solidly established practice that the world cannot live without. One of the established guidelines for accountants is called GAAP (Generally Accepted Accounting Principles in the US), and there are similar international setups. You might guess these standards are about rules, but actually, accounting is much […]
Now is the Time: Perspectives on the Challenges and Value of Metadata
Click to learn more about author David Schott In the era of publishing’s emergent global digital marketplace, many organizations are struggling with strategic questions about how to change their approach, planning, and execution around creating and managing their metadata. In the traditional publishing world, a significant portion of the metadata created and stored was on […]
Next and Prior: Pointing in Data Models
Click to learn more about author Thomas Frisendal. Pointers have been in and out of data models. From the advent of the rotating disk drive in the 60s and until around 1990, pointers were all over the place (together with “hierarchies”, which were early versions of aggregates of co-located data). But relational and SQL made them […]
Design Thinking Data Models
Click to learn more about author Thomas Frisendal. I seriously believe, and I also know from professional experiences that Design Thinking is the secret sauce for creating high quality Data Models. This sounds contra intuitive, so we will have to do some debunking: ”Design Thinking – isn’t that for designing good looking products, like watches, […]
How Not to Get Lost in 2018 with Knowledge Graphs: Map, Graph, Go!
Click to learn more about author Thomas Frisendal. Losing your way is easy. Much of Data Modeling in the search, analytics and reporting spaces have been focused on the fabulous five W-words. The hope is to try to answer the Why-question: We have been throwing technologies at this for quite some years now: Plain old […]
Say No More: Verbal Data Models
Click to learn more about author Thomas Frisendal. ”Nudge nudge, wink wink, say no more, say no more”. Says British Eric Idle in the third Monty Python’s Flying Circus episode, “How to Recognise Different Types of Trees From Quite a Long Way Away” from 1969. Indeed, it should not be necessary to say more, once […]
Standardizing Data Management and Data Governance Services (A First Look)
Click to learn more about author Tejasvi Addagada. The needs of organizations mostly financial services and health care providers are seeing an increased necessity to manage the data as an Enterprise asset, as regulations and policy around data are quickly evolving. Although regulation is one of the primary drivers, firms have started to appreciate the importance […]