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 ...

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 ...

Graph theory isn’t enough. The mathematical language for talking about connections, which usually depends on networks — vertices (dots) and edges (lines connecting them) — has been an invaluable way ...

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 ...

To help account for fuel distribution during combustion in diesel engines, a fuel film model has been developed and implemented into the KIVA-II code [1]. Spray-wall interaction and spray-film ...

A guide to the 10 most common data modeling mistakes Your email has been sent Data modeling is the process through which we represent information system objects or entities and the connections between ...

For decades, data centers were designed with permanence in mind: fixed plans, rigid shapes and predictable life cycles. Physical constraints of legacy architectures made them inherently static. But in ...

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 ...