Introduction to Paper Presentation on Data Warehouse and Data Mining:

It is a collection of the data in support of management decision making, it is subject oriented, time variant and non volatile. It is a multi dimensional database and it can be categorized in three categories they are Enter pries data warehouse in which data warehouse provides a central database for decision. Another is Operational data store (ODS) in which broad enterprise wide scope, and the third one is Data Mart which is a subset of data warehouse and it supports a particular region. This is built using dimensional data modeling where fact tables are connected with dimension tables.

Interface with other data warehouses: – it is likely to be interfaced with other applications that use it as the source of operational system data. It can be a better single and consistent source for many kinds of data than the operational systems.

Four ways to build a data warehouse: – There are four kinds of approaches to build warehouse they are top-down, bottom-up, hybrid and federated.

Requirements: – It can exhibit performance and usage characteristics across a wide spectrum in which some are read-only and are designed for fast on-line query processing. It also has write-only. The two features of data warehouse are query performance and load performance.

Data mining: -it is the technique used for extracting using information from the large databases. This process is not simple because the user may determine that the selected data is of poor quality or it did not produce the results of the expected quality. It consists of hardware, software, “warm ware” (skilled labor).It also supports the transformation of data to information. The process of data mining include the most basic form of query and reporting, presenting the output in graphical, tabular and textual forms.

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