Data Mining Architecture

Components of data mining systems are a Data source, Data mining engine, data warehouse server, the pattern evaluation module, graphical user interface, and Knowledge base.

Data Source

The data sources define where the database tables reside and where the software runs logic objects for the enterprise. Data warehouses may comprise one or more databases, text files spreadsheets, or other repositories of data.
Sometimes, even plain text files or spreadsheets may contain information. Another primary source of data is that the World Wide Web or the web. Data sources can point to a database during a specific location.

Passing the data to the database or data warehouse server, the information must be cleaned, integrated, and selected because the information comes from various sources and in several formats, it cannot be used directly for the data mining procedure because the data may not be complete and accurate. The Primary data requires to be cleaned and unified.
More information than needed are going to be collected from various data sources, and only the data of interest will need to be selected and passed to the server. These procedures aren't as easy as we expect . Several methods could also be performed on the data as a part of selection, integration, and cleaning.

The server consists of the first data that's able to be processed. The server is cause for retrieving the relevant data that's supported data mining as per user request.

Data mining Engine is that the major component of our data mining architecture. It comprises instruments and software wont to obtain insights and data from data collected from various data sources and stored within the data warehouse.
It contains several modules for operating data mining tasks, including association, characterization, classification, clustering, prediction, time-series analysis, etc.

It collaborates the data mining engine to focus the search on exciting patterns. Pattern evaluation module primarily responsible for the measure of investigation of pattern by using threshold value.

This module helps the user to simply and efficiently use the system without knowing the complexity of the method .
Graphical interface (GUI) module communicates between the data mining system and therefore the user.
It cooperates with the data mining system when the user specifies a question or a task and displays the results.

Knowledge base is useful within the entire process of data mining. It'd be helpful to guide the search or evaluate the stake of the result patterns. Knowledge base may even contain user views and data from user experiences which may be helpful within the data mining process.
The data mining engine may receive inputs from the Knowledge base to create the result more accurate and reliable.
Pattern assessment module regularly interacts with the Knowledge base to get inputs, and also update it.