Introduction to Data Mining and Warehousing PPT Presentation:

Introduction to Data mining and warehousing:

Data mining and warehousing is the technique of extracting the predictive information from the present large databases. So it is very difficult for the human analysts to make decisions patterns with the huge data so data ware housing and data mining concepts are used to increase the performance. By using Data warehousing a relational database is created for performing the query and analysis instead task processing. In this paper we will discuss the areas of implementation of data mining and warehousing techniques to increase the business performance.

Brief on Data warehousing and mining techniques:

In Data mining the huge databases are analyzed into useful information based on different perspectives. Depending upon the consumer preferences and logical the data is grouped and divided into clusters. By using the data mining algorithms we can easily track the model scores and we can easily reconstruct the consumer preferences based on the demand.

Data warehousing is the relational database which contains historical data derived from the transaction process and from the underlined data sources materialized views are generated which is used for speeding up the query process. In data warehousing accessing base relations are distributed among various sources so the data bases may unavailable sometimes due to the relations.

Conclusions:

By using the data mining and ware housing techniques we increase the productivity in the decision making and we can make substantial and accurate analysis. Data mining and warehousing techniques are highly scalable and they load performance. These techniques are used in security fields for face recognition mechanism and in judiciary purposes for giving judgment to similar cases and in Biometrics and web store designs.

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