What are the data mining interfaces?

Data mining is the process of finding useful new correlations, patterns, and trends by transferring through a high amount of data saved in repositories, using pattern recognition technologies including statistical and mathematical techniques.

It is the analysis of factual datasets to discover unsuspected relationships and to summarize the records in novel methods that are both logical and helpful to the data owner.

It is the procedure of selection, exploration, and modeling of high quantities of information to find regularities or relations that are at first unknown to obtain clear and beneficial results for the owner of the database.

By outsourcing data mining, all the work can be done quicker with low operation costs. Specific firms can also use new technologies to save data that is impossible to find manually. There are tonnes of data available on multiple platforms, but very limited knowledge is accessible.

The data mining interface provides the medium that allows users to communicate with data mining processes. It is difficult to use data mining query language. A graphical user interface can be used to communicate with data mining systems. A data mining query language can serve as a core language, on top of which GUIs can easily be designed.

Data mining can consist of the following functional components which are as follows −

Data collection and data mining query composition − It allows users to specify task-relevant data sets and to compose data mining queries.

Presentation of discovered patterns − It allows the display of discovered patterns in various forms like tables, graphs, charts, and other visualization techniques.

Hierarchy specification and manipulation − It allows to do the specification of concept hierarchy, either manually or automatically. It also allows the concept hierarchies to be modified or adjusted automatically based on a given data set distribution.

Manipulation of data mining primitives − It enables the powerful adjustment of data mining operations such as selection, display, and alteration of concept hierarchies.

Interactive multilevel mining − It enables the roll-up or drill-down operations on identified patterns. The design of data mining interfaces should also consider the different classes of users. Users of the data mining system can be classified such as business analysts and business executives.

Business analysts want the flexibility and convenience in selecting different portions of data, manipulating dimensions, and tuning data mining processes. On the other hand, business executives need clear presentation and interpretation of data mining results, easy integration of data mining results into report writing and presentation process. A well-designed data mining system should provide user-friendly interfaces for both kinds of users.