Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

Data modeling, at its core, is the process of transforming raw data into meaningful insights. It involves creating representations of a database’s structure and organization. These models are often ...

Organizations often force the DBA to take on the job of data modeling. That does not mean that DBAs are well-trained in data modeling, nor does it mean that DBAs are best suited to take on this task.

With the growing interest in adopting best practices across IT departments, particularly according to standards such as the Information Technology Infrastructure Library (ITIL), many organizations are ...

When we build database-backed enterprise applications, we generally want to isolate our entity models, the DbContext, and the logic for database initialization and migration to maintain a clean ...

Forbes contributors publish independent expert analyses and insights. I write about how to drive more value with data and analytics. Most organizations have invested heavily in using data to enhance ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...

MongoDB MDB and Oracle ORCL are capitalising on the intersection of cloud migration and artificial intelligence to drive ...