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Data Mining Terminologies | Data Mining Glossary of Terms

This page on Data Mining terminologies covers very useful data mining related terms. This data mining glossary is very useful for beginners to this domain.

Following table mentions terminologies related to the data mining domain.

Data Mining terminologies Description
Data Mining It refers to extraction of desired information from huge data available in www or databases. It has many applications of which few of them are market analysis, customer retention, fraud detection, science exploration, disease analysis etc.
Data Mining Engine It is the main component in data mining system. It performs many core functions viz. association, classification, characterization, prediction, cluster analysis etc.
Knowledge Base It is the storage based on the pattern search like cache in the computer network. This helps in providing quick results for the search when similar patterns are being searched in the future.
Knowledge discovery It has broad functionalities which include data cleaning, data selection, data integration, data transformation, data mining, pattern evaluation etc.
Data Warehouse It is constructed by integration of data from multiple heterogeneous sources. It supports various tasks such as analytical reporting, adhoc and/or structured queries, decision making etc.
User Interface This is the interface part between user and data mining system. It helps in fulfilling requirements of the user from the data mining system. It helps in providing information relevant to the search pattern, helps in visualing patterns in various forms, sorting out data based on need from different databases and integrating it as per desired formats etc.
Data Cleaning It is the process which removes noisy data and correct any inconsistencies in the data. It is the process which is applied before data warehousing or data storage. It basically does transformations on the data to provide correct datasets.
Data Selection The process of retrieving relevant data from databases for analysis purpose is known as data selection.
Data Integration The collection and aggregation of appropriate data as per need is known as data integration.
Data Transformation The change in form or syntax of the data is known as data transformation.
Clusters It refers to group of similar kind of objects. Objects in one cluster is different compare to objects in the other cluster.
OLAP On-Line Analytic Processing
OLTP On-line Transaction Processing
OLAM Online Analytical Mining
KDD Knowledge discovery in databases
MDDB multidimensional database

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Refer data mining tutorial>> which describes data mining applications, data mining working with architecture, data mining advantages etc.

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