Data models provide the conceptual tools for describing the model of an information system at the data abstraction level. It enables users to decide how data will be stored, leveraged, updated ...

These top data modeling tools and applications enable users to build conceptual and logical data models that deliver significant competitive advantage. Written by eWEEK content and product ...

Relational data modeling is fine as long as data is being stored in a relational database, but otherwise it has no particular use. And XML cannot credibly be called a modeling language.

The PR rep said, “The heyday of the 30-year-old relational database is over, and Oracle has missed the shift to next-generational database technology needed to meet today’s big data challenges ...

SqlDBM unveils the first all-in-one relational and transformational modeling platform. The addition of Transformational Modeling, Tx, allows data teams to simplify, automate, and collaborate on ...

Data models are used to represent real-world entities, but often have limitations. Avoid common data modeling mistakes for data integrity.

Big data is less predictable than traditional data, and therefore requires special consideration when building models. Here are some things to keep in mind. Image: iStock/z_wei Data modeling is a ...

Forecasting is a fundamentally new capability that is missing from the current purview of generative AI. Here's how Kumo is changing that.

Coverage includes the data modeling process, basic relational model, normalization theory, relational algebra, and mapping a data model into a database schema. Structured Query Language is used to ...

Relational databases are well-suited to conventional data analysis such as reporting and classical statistical analysis (what you learned in the college Statistics 101 class, for example).