Working of Data Mining with requirements

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SOFTWARE REQUIRED:

SQL Server Setup requires Microsoft Windows Installer 3.1 or later and Microsoft Data Access Components (MDAC) 2.8 SP1 or later.

SQL Server Setup installs the following software components required by the product:
  • Microsoft .NET Framework 2.0
  • Microsoft SQL Server Native Client
  • Microsoft SQL Server Setup support files
            DATA MINING:

Data mining is a key member in the Business Intelligence (BI) product family in SQL Server 2005. Data mining is about analyzing data and finding hidden patterns using automatic or semiautomatic means, which can be explored for valuable information. It is about learning the characteristics of data set, which are not possible to discover by simple seeing.
There are several attempts to define the learning task applied to software systems such as:  "Learning is any process that enables a system to achieve a better performance when working on the same task" or "Learning consists of constructing or modifying representations of past experience".
Large volumes of data which comes from information systems have been accumulated and stored in databases. Organizations have become data-rich and knowledge-poor. The information found in the patterns can volumes of data which comes from information systems have been accumulated and stored in databases. Organizations have become data-rich and knowledge-poor. The information found in the patterns can be used for reporting, and, most importantly, for prediction.

WORKING WITH DATA MINING:

Data mining approach in Analysis Service is rather simple, all you need to do is to select the right data mining algorithm and specify the input columns and the predictable columns (which are the targets for the analysis).
Data mining can be used to solve a several problems such as:
  • Classification: Classification refers to assigning cases into categories based on a predictable attribute.
  • Clustering: It is used to identify natural groupings (self-similarity groups) of cases based on a set of attributes.
  • Large volumes of data which comes from information systems have been accumulated and stored in databases. Organizations have become data-rich and knowledge-poor. The information found in the patterns can be used for reporting, and, most importantly, for prediction.