DATA MINING

Introduction
The process of analyzing data form different perspectives and summarizing it into useful information that can be used to bring the solution of the different problem so the to bring changes is important to us. Software in one of a number of analytical tools for analyzing data.

At before:
Human have been manually extracting information from data for centuries, but due to the increase of data volumes in modern times people discover a new method called the automatic approaches.

Data mining technically, is the process of extracting the hidden patterns from large amount of data, also the process of finding corrections or pattern among dozens in large relational database.

How data mining work
Information technology has been evolving separate transaction and analytical systems data mining provides the link between the, Data mining software analyzes relationships and patterns in stored transaction data based on open-ended user queries. Several types of analytical software are statistical, machine learning, and neural networks.
Forms of data mining different data can be created from different source or forms which are

Ø Text mining is the process of deriving high quality information from text. High quality information is typically derived through the dividing of pattern and trends through means such as statistical pattern learning.

Ø Audio mining the content of an audio signal can be automatically analyzed and searched, commoly used in the field of automatic speech recognition.
Ø Relational database and social network data mining

Video data mining through watching video different information can be obtain
Ø Image data mining is another form of data where by information can be found
Ø Wed data mining the application of data mining in the extraction of the hidden data from the web
Also there are stages of data mining which are
Ø Exploration: this stage usually starts with data preparation which involves cleaning data and data transformation.

Ø Model bailing and validation: this stage involves considering various models and choosing the best one based on their predictive performance.

Ø Deployment: this is the final stage which involves using the model selected as best in the previous stage and applying it to new data in order to generate predictions or estimates of the expected outcomes.

Extraction of data from different source is important in marking, banking, law enforcement and researchers. The information that obtain can help researchers and menagengment to come out with the report and the solution of the different issues concerned. Also it is disadvantage in security issues, misuse of information and privacy issues.