Click to learn more about author Thomas Frisendal. At the DATAVERSITY® Graphorum Conference in Chicago in October I attended Dave McComb’s tutorial on “Data-Centric: Models and Architectures”. At the end, he ran a raffle for his 2018 book, Software Wasteland – How the Application-Centric Mindset is Hobbling our Enterprises (TechnicsPub). I was the lucky winner! […]
Knowledge Graphs and Data Modeling
Click to learn more about author Thomas Frisendal. Trip Report From Graphorum / Data Architecture Summit 2019 On October 14th thru 17th Chicago hosted the two co-located conferences Graphorum and Data Architecture Summit 2019 by DATAVERSITY®. It was two days of good tutorials and two good days of conference presentations. One thing to think about […]
Red Hat Brings Predictive Models to Business Automation Portfolio
A recent press release reports, “Red Hat, Inc., the world’s leading provider of open source solutions, today announced the latest release of Red Hat Process Automation, unveiling new applied artificial intelligence (AI) capabilities for predictive decision modeling, and support for the development of process- and decision-based business applications using micro-frontend architectures. Together with additional enhancements […]
“What is…?”: Build Your Own Bundle
DATAVERSITY Online Training – Professional Education at Your Convenience Individual Course Price: $49 Purchase 2-5 Courses: 10% discount Purchase 6-10 Courses: 15% discount Purchase 11+ Courses: 20% discount The “What is…?” series of introductory data courses are designed to be short, informational trainings that give a topic-focused overview for the non-data professional. This option enables […]
What is Multiple Linear Regression Analysis?
Click to learn more about author Kartik Patel. Multiple Linear Regression is a statistical technique that is designed to explore the relationship between two or more variables (X and Y). It is useful in identifying important factors (X) that will impact a dependent variable (Y) and the nature of the relationship between each of the factors […]
Open Data Group Rebrands as ModelOp, Puts AI and ML Models in Business at Scale
According to a new press release, “Open Data Group (ODG) has rebranded as ModelOp, reflecting the company’s sole focus on Model Operations and the rapidly growing need in large enterprises for this critical new capability, which is essential for realizing the value from their investments in AI. According to Gartner, ‘The democratization of ML techniques […]
Modeling Misfit Types: Why Type Inheritance Is Not a Good Fit in Data Models
Click to learn more about author Thomas Frisendal. “Complete Consistence” Drives Temporality, … And What Else? In August I published a blog post called The Future History of Time in Data Models. The short version of that story is that if you aim for “Complete Consistence for Temporal Extensions”, you need to work on the […]
Data Modeling in an Agile World
Data Modeling creates a model for storing and processing data that works in a predictable, consistent manner. It includes the visual presentation of data structures, while enforcing business rules and government policies. A data model focuses on the needed data and its organization, rather than the operations performed on the data. Data Modeling is done […]
The Future History of Time in Data Models
Click to learn more about author Thomas Frisendal. Timely Concerns in Data Models In June I published a blog post called Timely Concerns in Data Models. In summary the concerns that I mentioned in June were: Roles of time (such as Valid Time, Recorded Time, As-Is vs. As-Of, Read timelines, Time Series), The scope of […]
The History of Time in Data Models
Click to learn more about author Thomas Frisendal. In my last blogpost Timely Concerns in Data Models, we looked at the basic challenges of dealing with time dependencies in Data Modeling. I promised to continue this quest by going over the history of these issues. How well have we actually solved these challenges? So, hop […]