Data mining is a valuable technology in many application domains. It has become increasingly indispensable in the private sector as a tool for optimizing operations and maintaining a competitive edge. Data mining also has critical applications in the public sector and in scientific research. However, the complexities of data mining application development and the complexities inherent in managing and securing large stores of data can limit the adoption of data mining technology.
Oracle Data Mining is uniquely suited to addressing these challenges. The data mining engine is implemented in the Database kernel, and the robust administrative features of Oracle Database are available for managing and securing the data. While supporting a full range of data mining algorithms and procedures, the API also has features that simplify the development of data mining applications.
The Oracle Data Mining API consists of extensions to Oracle SQL, the native language of the Database. The API offers the following advantages:
Scoring in the context of SQL queries. Scoring can be performed dynamically or by applying data mining models.
Automatic Data Preparation (ADP) and embedded transformations.
Model transparency. Algorithm-specific queries return details about the attributes that were used to create the model.
Scoring transparency. Details about the prediction, clustering, or feature extraction operation can be returned with the score.
A workflow-based graphical user interface (GUI) within Oracle SQL Developer. You can download SQL Developer free of charge from the following site:
http://www.oracle.com/pls/topic/lookup?ctx=db121&id=datminGUI
Note:
A set of sample data mining programs ship with Oracle Database. The examples in this manual are taken from these samples. See The Data Mining Sample Programs for more information.
See Also:
Oracle Data Mining Concepts Part I for an introduction to Oracle Data Mining