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In this article, Pipe summarizes that the managers of the data warehouse use the technical metadata, e.g., the sources of the data, the data cleansing or enhancement rules, and the destination of the data, etc. (Pipe, 1997). The technique of Metadata usage makes business decisions on facts and not on intuition. This is applicable to both tactical and strategic business decisions. Pipe stated that if viewed intelligently and with imaginative mind, it helps the users to sense early warning on some aspects of business, calling for business review and radical change in policy, rule and strategies.

Article 8: Refreshing Data Warehouses with Near Real-Time Updates by Rahman, Nayem in 2007.

In 2007, Rahman, Nayem was given an article “Refreshing Data Warehouses with Near Real-Time Updates”. In tactical and strategic management support system, data warehouse has proved to be the chief component (Rahman, 2007). For the analysis of the historical information, data warehouse was used in conventional decision support systems. Earlier, it was easy to keep the record of the acquired data and maintain activities on the basis of demand. During that time, batch windows were used at night when the users of the business reached home. In order to make strategic business decisions, decision makers require cutting-edge information, therefore; there is a need to refresh the data ware house many times in a day (Rahman, 2007). In near real-time decision support system, the data warehouses are reviewed by using metadata model and it also enhances the frequency of batch cycle runs.

A Real Time Data Warehouse shows an analytical constituent of an enterprise or project level data stream. The data stream plays an important role, as it endures asynchronous, nonstop and multi-point deliverance of data. The movement of data is from the source of origin to all uses, which do not need any kind of staging. Once the writing of original data is completed, the movement of data takes place. The delay in time is accounted to the transport latency to send off the case of data being rendered. Respondents who perform near real-time data warehousing has increased from 2 percent to 24 percent in a period of 18 months. The complete application is reserved coherent by means of these real-time updates (Ramamritham, et al, 1996).

Article 9: A Comparison of Data Warehousing Methodologies by Arun Sen and Atish P. Sinha in 2005.

This article was written by Sen and Sinha in the year 2005. The article explains that the data warehousing has been quoted as the post-millennium project with highest-priority with more than half of IT executive's (Sen & Sinha, 2005). To support the growing market, a large number of data warehousing methodologies and apparatuses are available. A major concern for many firms is to choose a tool from various methodologies which can be easily employed in a given data warehousing project (Sen & Sinha, 2005). This article evaluates and assesses various important data warehousing methodologies based on a common set of attributes.

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