Explain the architecture of data mining system with block diagram./Describe the Data Mining Architecture with figure.

Data Mining Architecture

The process of extracting information to identify patterns, trends, and useful data that would allow the business to take the data-driven decision from huge sets of data is called Data Mining. The data mining process involves several components, and these components constitute a data mining system architecture. The significant 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.

The major component of a data mining system architecture is as follows:-

• Database, Data Warehouse, or Other Information Repository: This is one or a set of databases, data warehouses, spreadsheets, or other kinds of information repositories. Data cleaning and data integration techniques may be performed on the data.

• Database or Data Warehouse Server: It fetches the data as per the users’ requirement which one needs for data mining task.

• Knowledge Base: This is the domain knowledge that is used to guide the search or evaluate the interestingness of resulting patterns. It is simply stored in the form of a set of rules. Such knowledge can include concept hierarchies, used to organize attributes or attribute values into different levels of abstraction.

• Data Mining Engine: This is essential to the data mining system and ideally consists of a set of functional modules for tasks such as characterization, association and correlation analysis, classification, prediction, cluster analysis, outlier analysis, and evolution analysis.

• Pattern Evaluation Module: This component typically employs interestingness measures and interacts with the data mining modules so as to focus the search toward interesting patterns. It may use interestingness thresholds to filter out discovered patterns.

• Graphical User Interface: This module communicates between users and the data mining system, allowing the user to interact with the system by specifying a data mining query or task. In addition, this component allows the user to browse database and data warehouse schemas or data structures, evaluate mined patterns, and visualize the patterns in different forms. 

                                 OR IN LONG,

Data mining is a very important process where potentially useful and previously unknown information is extracted from large volumes of data. There are a number of components involved in the data mining process. These components constitute the architecture of a data mining system.

Data Mining Architecture

The major components of any data mining system are data source, data warehouse server, data mining engine, the pattern evaluation module, graphical user interface, and knowledge base.

a) Data Sources

Database, data warehouse, World Wide Web (WWW), text files and other documents are the actual sources of data. You need large volumes of historical data for data mining to be successful. Organizations usually store data in databases or data warehouses. Data warehouses may contain one or more databases, text files, spreadsheets, or other kinds of information repositories. Sometimes, data may reside even in plain text files or spreadsheets. The World Wide Web or the Internet is another big source of data.

Different Processes

The data needs to be cleaned, integrated, and selected before passing it to the database or data warehouse server. As the data is from different sources and in different formats, it cannot be used directly for the data mining process because the data might not be complete and reliable. So, first data needs to be cleaned and integrated. Again, more data than required will be collected from different data sources and only the data of interest needs to be selected and passed to the server. These processes are not as simple as we think. A number of techniques may be performed on the data as part of cleaning, integration and selection.

b) Database or Data Warehouse Server

The database or data warehouse server contains the actual data that is ready to be processed. Hence, the server is responsible for retrieving the relevant data based on the data mining request of the user.

c) Data Mining Engine

The data mining engine is the core component of any data mining system. It consists of a number of modules for performing data mining tasks including association, classification, characterization, clustering, prediction, time-series analysis, etc.

d) Pattern Evaluation Modules

The pattern evaluation module is mainly responsible for the measure of the interestingness of the pattern by using a threshold value. It interacts with the data mining engine to focus the search towards interesting patterns.

e) Graphical User Interface

The graphical user interface module communicates between the user and the data mining system. This module helps the user use the system easily and efficiently without knowing the real complexity behind the process. When the user specifies a query or a task, this module interacts with the data mining system and displays the result in an easily understandable manner.

f) Knowledge Base

The knowledge base is helpful in the whole data mining process. It might be useful for guiding the search or evaluating the interestingness of the result patterns. The knowledge base might even contain user beliefs and data from user experiences that can be useful in the process of data mining. The data mining engine might get inputs from the knowledge base to make the result more accurate and reliable. The pattern evaluation module interacts with the knowledge base on a regular basis to get inputs and also to update it.

Summary

Each and every component of the data mining system has its own role and importance in completing data mining efficiently. These different modules need to interact correctly with each other in order to complete the complex process of data mining successfully.