Data Modeling describes the plans and activities around diagramming data requirements for business operations across one or more systems. This blueprint defines unique data entities (such as tables, systems, concepts, and hubs) and their characteristics (such as inheritance, importance, and physical structures) along with how the data flows between entities. Organizations create or update data models anytime, depending […]
Data Provisioning: Ingest, Curate, and Publish
A collection of facts from which inferences can be made is called data. It is the basis on which factual information is derived, providing relevant results to the end users. Data is the cornerstone of contemporary society and is crucial to many facets of people’s lives. In order to gain knowledge and make wise decisions, […]
How to Become a Data Modeler
There is always a need for data modelers. However, the job description of this career field varies, depending on the needs of the organization. For example, if you become a data modeler working for a startup, you might coordinate with data scientists and data architects in designing a new system – one that includes the […]
Generative AI and Semantic Compliance
Only CPT and its peers know how many statements have been made based on results from generative AI. But there are loads of them. My background as a data modeler over many years makes me shiver a little bit, because what the friendly AI helpers help us produce is subjected to cognitive processes, where we, the readers, process […]
Data-Ed Webinar: Conceptual vs. Logical vs. Physical Data Modeling
Download the slides here>> About the Webinar A model is developed for a purpose. Understanding the strengths of each of the three Data Modeling types will prepare you with a more robust analyst toolkit. The program will describe modeling characteristics shared by each modeling type. Delegates will be able to trace model components as […]
A Brief History of Data Modeling
Data Modeling is the “act” of creating a data model (physical, logical, conceptual, etc.) and includes defining and determining an organization’s data needs and goals. The act of Data Modeling defines not just data elements, but also the structures they form and the relationships between them. Developing a data model requires the data modelers to work […]
Should You Consider a Unified Data Model?
A unified data model allows businesses to make better-informed decisions. How? By providing organizations with a more comprehensive view of the data sources they’re using, which makes it easier to understand their customers’ experiences. A singular, interrelated network that’s connected to one source of truth gives organizations a more efficient, accurate, and comprehensive analysis of […]
Modeling Modern Knowledge Graphs
In the buzzing world of data architectures, one term seems to unite some previously contending buzzy paradigms. That term is “knowledge graphs.” In this post, we will dive into the scope of knowledge graphs, which is maturing as we speak. First, let us look back. “Knowledge graph” is not a new term; see for yourself […]
Connecting the Three Spheres of Data Management to Unlock Value
Many organizations have mapped out the systems and applications of their data landscape. Many have documented their most critical business processes. Many have modeled their data domains and key attributes. But only very few have succeeded in connecting the knowledge of these three efforts. The remainder of this point of view will explain why connecting […]
Achieving Smoother, Quicker Data Modeling
When the Navy SEALS embraced its motto, “Slow is smooth, and smooth is fast,” they may as well have been discussing building data models in the same breath. The SEALS chose the phrase to remind its participants not to rush but to act thoughtfully and deliberately. Data Modeling does the same thing by helping businesses design and update data architectures […]