Introduction to data mining

Data Mining

Data mining is the process of searching, collecting and analyzing a large amount of data from data bases to discover the hidden patterns and relationships. As the data volume production is increasing for every year , data mining is gaining more importance. Many organization and businesses  collects and examine the data on their relative operations in order to make their business successful.

Simply data mining can apply to any businesses and organization to produce profitable and predictable outcomes.  Here are some real time applications for data mining

  • Service providers
  • Retail
  • E commerce
  • Super markets
  • Crime agencies

data mining

 

How does data mining works ?

Several types of data mining softwares are available for analyzing the relationships and patterns . They are statistical, machine learning, neutral networks. Generally four types of information can be find using these softwares

  • Classes which stored data can be used to locate data in predetermined groups
  • Clusters where data items are grouped according to the customer preferences
  • Associations which data can be mined to identify the associations
  • Sequential patterns where data can be mined for behavior patterns and trends

Data mining techniques:

There are many types of data techniques available based on the attributes and type of knowledge required from the data mining model

  • Predictive modeling which is used to estimate the target of particular attribute.
  • Descriptive modeling, the patterns discovered by analyzing the data will be used to determine the groups and also divides the data into groups.
  • Pattern mining which concentrates on rules where it describes specific patterns within the data
  • Anamoly detection is for finding data instances that are unusual and don’t fit for established patterns.

Simply data mining enables faster and cheaper computer with more storage and advanced computer algorithms. The results of data mining will be profitable and targets potential customers.

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