A Comparative Analysis of Traditional and Cloud Data Warehouse

Khawaja Ubaid ur Rehman, Umair Ahmad, Sajid Mahmood


In the age of emerging technologies, the amount of data is increasing very rapidly. With the passage of time, the methods of data handling are getting improved. Prediction analysis is quite a tough task, but it also yields interesting results. Different sectors like financial services, transportation, health and education are generating large amount of data. The emergence of web 2.0 (social web) made it possible for users and researchers to analyze and predict huge amount of data. The domain of Business Intelligence is core technology for users who want to extract useful information for decision making regarding their businesses. Data warehouse provides an insight into the business processes using the historical data. However, traditional data warehouse may not be suitable for the data analysis needs because of the evolving requirement of industry. It cannot be scaled up or down. Moreover, it cannot handle the increasing number of users. A new kind of data warehouse with design and implementation aspects has been emerged, called as cloud data warehouse. The cloud data warehouse model has evolved with the passage of time, which affects the application and business domains as well. The cloud data warehouse has evolved to control the large scale data. It can be scaled up or down at any time and also it has no limitation on increasing number of users. In this review paper, we have compared traditional and cloud data warehouse. We can conclude that the ultimate future of data warehouse is cloud data warehouse.

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DOI: http://dx.doi.org/10.21015/vtcs.v15i1.487


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