Data Warehouse

Dramatic advances in data capture, processing power, data transmission, and storage capabilities are enabling organizations to integrate their various databases into data warehouses. Data warehousing is defined as a process of centralized data management and retrieval. Data warehousing, like data mining, is a relatively new term although the concept itself has been around for years.
Data warehousing represents an ideal vision of maintaining a central repository of all organizational data. Centralization of data is needed to maximize user access and analysis. Dramatic technological advances are making this vision a reality for many companies. And, equally dramatic advances in data analysis software are allowing users to access these data freely. The data analysis software is what supports data mining. Hence, data warehousing provides the enterprise with a memory. Data mining provides the enterprise with intelligence.
Data warehouse is an enabled relational database system designed to support Very Large Databases (VLDB) at a significantly higher level of performance and manageability. Data warehouse is an environment, not a product. It is an architectural construct of information that is hard to access or present in traditional operational data stores.

Any organization or a system in general is faced with a wealth of data that is maintained and stored, but the inability to discover valuable, often previously unknown information hidden in the data, prevents it from transferring these data into knowledge or wisdom. To satisfy these requirements, these steps are to be followed.

Capture and integrate both the internal and external data into a comprehensive view "Mine" for the integrated data information
Organize and present the information and knowledge in ways that expedite complex decision making.

Access Tools for Data Warehousing

The principal purpose of data warehousing is to provide information to users for strategic decision making. These users interact with the data warehouse using front-end tools. Many of these tools require an information specialist, although many end users develop expertise in the tools. The access tools are divided into five main groups.

Data query and reporting tools
Application development tools
Executive information system (EIS) tools
Online analytical preprocessing tools and
Data mining tools

Data mining tools are considered for information extraction from data. In recent research, data mining through pattern classification is an important area of concentration.

Access Tools for Data Warehousing

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