The decision making processes need to reflect changes in the business world in a multidimensional way. This paper includes also similar way of viewing the data for carrying out key decisions that ...

Dimensional modeling is used to optimize a database so that data can be retrieved faster. A Dimensional Model is created using “fact” and “dimension” tables developed by Ralph Kimball.

Dimensional data modeling schemas enforce data quality before loading into Facts and Dimensions. Dimension and Fact are tied up by foreign keys that constrain referential integrity checks to prevent ...

In This Chapter The Multidimensional Data Model In the past decade, Microsoft SQL Server Analysis Services established itself as one of the leaders in the Business Intelligences systems market.

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 ...

As organizations undergo digital transformation, the importance of leveraging structured, multidimensional data and AI will continue to grow.

This is especially true for high dimensional data in which there are more parameters than observations. We discuss a score test on a hyperparameter in an empirical Bayesian model as an alternative to ...