Data Mining

• Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.

• Data mining is an interdisciplinary subfield of computer science with an overall goal to extract information (with intelligent method) from a data set and transform the information into a comprehensible structure for further use.

• Data mining is the analysis step of the "knowledge discovery in databases"  Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.

The major steps involved in a data mining process are:-

• Extract, transform and load data into a data warehouse.

• Store and manage data in a multidimensional databases.

• Provide data access to business analysts using application software.

• Present analyzed data in easily understandable forms, such as graphs.

• The first step in data mining is gathering relevant data critical for business. Company data is either transactional, non-operational or metadata. Transactional data deals with day-to-day operations like sales, inventory and cost etc. Non-operational data is normally forecast, while metadata is concerned with logical database design.

• Patterns and relationships among data elements render relevant information, which may increase organizational revenue. Organizations with a strong consumer focus deal with data mining techniques providing clear pictures of products sold, price, competition and customer demographics.

• The second step in data mining is selecting a suitable algorithm - a mechanism producing a data mining model. The general working of the algorithm involves identifying trends in a set of data and using the output for parameter definition.

• The most popular algorithms used for data mining are classification algorithms and regression algorithms, which are used to identify relationships among data elements. 

• Major database vendors like Oracle and SQL incorporate data mining algorithms, such as clustering and regression tress, to meet the demand for data mining.

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