A dimensional model is a type of data model that is less rigid and structured than other types of models. It is best for a contextual data structure that is more related to the business use or ...

Dimensional data modeling helps developers create and design databases and Schemas easily interpreted by business users. The relationship between dimensions and facts is fairly simple to read and ...

By implementing dimensional modeling, businesses can report, query, and analyze data. Facts, dimensions, and attributes make up the core of dimensional modeling. Facts are categorised as additive, ...

Conclusively, Multi-Dimensional Modeling plays a crucial role in empowering decision-making and driving process improvements in enterprise data management. By providing a comprehensive view of data ...

In high-dimensional data analysis, we propose a sequential model averaging (SMA) method to make accurate and stable predictions. Specifically, we introduce a hybrid approach that combines a sequential ...

More information: HyoJae Lee et al, A novel encoding method for high-dimensional categorical data for electricity demand forecasting in distributed energy systems, Applied Energy (2025).

Inmon versus Kimball is one of the biggest data modelling debates among data warehouse architects. Here is some help to select your own approach.