A data model is a visual representation of data elements and the relations between them.

Identify the core functionalities of data modeling in the data mining pipeline. Apply techniques that can be used to accomplish the core functionalities of data modeling and explain how they work.

MarketingProfs analyzes the nine most common data mining techniques used in predictive analytics, giving marketers a better way to drive success.

Missing data is a major issue in many applied problems, especially in the biomedical sciences. We review four common approaches for inference in generalized linear models (GLMs) with missing covariate ...

Incomplete data affects classification accuracy and hinders effective data mining. The following techniques are effective for working with incomplete data. The ISOM-DH model handles incomplete ...

Graph data modeling requires a different paradigm than modeling with Relational or other NoSQL databases. InfoQ spoke with Jim Webber and Ian Robinson about data modeling with Graph databases.

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