The design of a database determines what method is best suited for backing it up, and those methods vary quite a bit. In order to back up a database, you need to know how it’s delivered, but you also ...

AI is all about data, and the representation of the data matters strongly. But after focusing primarily on 8-bit integers and 32‑bit floating-point numbers, the industry is now looking at new formats.

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

What are the different types of predictive modeling? Your email has been sent Predictive modeling is a type of data mining that is used in a variety of situations and industries. This process involves ...

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 ...

eSpeaks' Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

Conceptual data models communicate a high-level perspective into the idea of the data under discussion. Because of this high-level nature, conceptual data models often lack much of the detail found in ...

Assuring data quality should be one of the most important goals for IT professionals. This is truer today than it has ever been as organizations rely on data to power their AI and machine learning ...

Distributed database consistency models form the backbone of reliable and high-performance systems in today’s interconnected digital landscape. These models define the guarantees provided by a ...

Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. Data is real. We enjoy the use of real world substantiated ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.