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Data Warehousing Features

Data warehouse is a subject oriented, time-variant, integration and non-volatile collection of data. An operational data base will be changed on account of transactions of the product. All the business helps and analyze with previous feedback on product data. It will be as a consumer data, supplier and finally execution will have no data that are available in analyzing because the previous data is updated due to various transactions. Data warehouse is consolidated and generalized data with multi variance view. It also provides also Online Analytical Processing (OLAP) tools. All these tools will help effectively and interactively with various spaces. This analysis will result in data generalization and mining of data. The main function of data mining is to classify associate, prediction and cluster. It is also integrated with operations of OLAP to enable the interactive mining of knowledge with various level of abstraction. So that’s the reason for data warehouse and has become as an important platform for OLAP and data analysis.

Data warehouse – understanding

  • A data warehouse is a database which is kept against the organization’s database.
  • No frequent update is done within the warehouse.
  • It is possible to consolidate historical data and also helps the business organization to do its own work.
  • A data warehouse also helps the data to take important decisions.
  • It also helps the system with integration and with application system.
  • It mainly helps the consolidated historical data analysis.

Features of data warehouse

Subject oriented: The main thing of data warehouse is subject oriented. It also provides as information through the organization operations. The subjects are for customers, suppliers, revenue and sales. A data warehouse does not mainly focus on operations rather than focusing on modeling. It is constructed for integrating data from heterogeneous sources like relational database, files and flat etc. It enhances with effective analysis of data.

Time variant: Here the data are collected in data warehouse and identified with certain time period. In a data warehouse all the data gives information from the historical view.

Non-volatile: It means the old data will not be erased when a new data is added. A data warehouse is kept separate from the operational database and with frequent changes in operational database and are not reflected with any other data warehouse. A data warehouse does not require any transaction process, concurrency and recover because it is stored in and separated from the operational database.

Applications of data warehouse

A data warehouse helps the business executives in organizing, using and analyzing the data by using decision making. It serves as a role part of a plan-executed with feedback system used in the enterprise management. Data warehousing are widely used in the following fields.

  • Retail sectors
  • Financial services
  • Controlled manufacturing and
  • Banking services

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