What are the components of data mining?

Data Mining 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.

Data mining is an interdisciplinary field, the assemblage of a set of disciplines, such as database systems, statistics, machine learning, visualization, and data science. It is based on the data mining methods used, approaches from other disciplines can be used, including neural networks, fuzzy and rough set theory, knowledge representation, inductive logic programming, or high-performance computing.

It is established on the types of data to be mined or on the given data mining application, the data mining system can also integrate methods from spatial data analysis, data retrieval, pattern identification, image analysis, signal processing, computer graphics, network technology, economics, business, bioinformatics, or psychology.

A data mining query language can be designed to incorporate these primitives, enabling users to flexibly connect with data mining systems. A data mining query language supports an authority on which user-friendly graphical interfaces can be constructed. This promotes a data mining system's communication with other data systems and its integration with the complete data processing environment.

It is designing an inclusive data mining language is challenging because data mining protects a wide spectrum of functions, from data characterization to evolution analysis. Each task has several requirements. The design of an effective data mining query language needed broad learning of the power, limitation, and underlying structure of the different types of data mining tasks.

Data mining functionalities are used to define the type of patterns that have to be discovered in data mining tasks. In general, data mining tasks can be classified into two types including descriptive and predictive. Descriptive mining tasks define the common features of the data in the database and the predictive mining tasks act inference on the current information to develop predictions.

The major components of data mining are as follows −

  • Databases − This is one or a set of databases, data warehouses, spreadsheets, and another type of data repository where data cleaning and integration techniques can be implemented.
  • Data warehouse server − This component fetches the relevant records based on users request from a data warehouse.
  • Knowledge base − It is a knowledge domain that is employed for discovering interesting patterns.
  • Data mining engine − It uses a functional module that is used to perform tasks including classification, association, cluster analysis, etc.
  • Pattern evaluation module − This component uses interestingness measures that communicate with data mining structure to target the search towards interesting patterns.
  • User interface − This interface enables users to interact with the system by describing a data mining function or a query through the graphical user interface.

Updated on: 15-Feb-2022

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