Data mining refers to extraction of information from large amount of data.
In today’s world data mining is very important because huge amount of data is present in companies and different type of organization. It becomes impossible for humans to extract information from this large data, so machine learning technology are used in order to process data fast enough to extract information from it.
Data mining is used by companies in order to get customer preferences, determine price of their product and services and to analyse market.
Data mining is also known as knowledge discovery in Database (KDD).
Data mining architecture has many elements like Data Warehouse, Data Mining Engine, Pattern evaluation,User Interface and Knowledge Base.
Data Mining Architecture
A data warehouse is a place which store information collected from multiple sources under unified schema. Information stored in a data warehouse is critical to organizations for the process of decision-making.
Data Mining Engine is the core component of data mining process which consists of various modules that are used to perform various tasks like clustering, classification, prediction and correlation analysis.
Pattern Evaluation is responsible for finding various patterns with the help of Data Mining Engine.
User Interface provides communication between user and data mining system.It allows user to use the system easily even if user doesn't have proper knowledge of the system.
Knowledge Base consists of data that is very important in the process of data mining.Knowledge Base provides input to the data mining engine which guides data mining engine in the process of pattern search.
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