This book offers a comprehensive framework for mastering the complexities of learning high-dimensional sparse graphical models through the use of conditional independence tests. These tests are ...

Abstract: We consider the problem of variable selection in classification for high dimensional spatially correlated data. Identification of reliable classification patterns is challenging due to the ...

At its heart, data modeling is about understanding how data flows through a system. Just as a map can help us understand a city’s layout, data modeling can help us understand the complexities of a ...

When dealing with data, you may have to know the fact table vs dimension table differences. A fact table holds the data that needs to be analyzed, and a dimension table stores data dealing with how ...

Yan, M. X. and Wang, H. L. (2026) Seismic Forward Modeling of the Lower Ordovician in the Northwestern Sichuan Basin. Journal ...

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 ...

The Data Warehouse Developer must have a sound understanding of BI best practices, relational structures, dimensional data modeling, structured query language (SQL) skills, data warehouse and ...