The 5 Data Warehouse System Architectures

by Hongde H
The peer reviewed article I choose to read this week is about comparison plan for data warehouse system architecture. As organizations, making good and fast decisions about their businesses is always one of the most important perspectives in leading the businesses to success. Therefore, making good use of data in proper way is what most organizations are looking for. And having a right data warehouse architecture and making good use of it benefits the businesses.

As what we are told in the article, data warehouse has unique features such as data mining and ad hoc querying on data collected and integrated from many of the computerized systems used in organization. Data warehouse can be built using a number of architectures. Each one of the architecture has its own pros and cons. In the article, author investigates five different data warehouse architectures: centralized data warehouse, independent data mart, dependent data mart, homogeneous distributed data warehouse and heterogeneous distributed data warehouse.

According to the article, a Centralized Data Warehouse is a sole physical database which contains business data for a specific utility area, department, branch, division or the whole enterprise. Centralized data warehouse serves the needs of several separate business unites simultaneously using a single data model that spans the need of multiple business divisions. In centralized data warehouse, all information systems located and managed from one physical location even if there are many data sources spread around the globe.

Independent data mart and dependent data mart are two ways of making use of data mart so that data can be retrieved easily. Independent data marts are standalone systems built by drawing data directly from operational or external sources of data, or both. Whereas, dependent data mart draw data from central data warehouse that has already been created. A data mart is a simple form of a data warehouse that is focused on single area such as Sales, Finance, or Marketing. Data marts are often built and controlled by a single department within an organization.

Homogeneous data warehouse and heterogeneous data warehouse are categorized as distributed data warehouse. A distributed data warehouse involves merging integration through the database element and distribution through the networking element. A homogeneous data warehouse integrates multiple data resources. Heterogeneous is categorized by the use of different Database Management Systems at the local sites.

Finally, I choose this article is because it is closely related what are lectured in the classes of the week. I suggest everyone to read the article besides this summary because I think the whole article will not only gives you a better understanding of how each architecture works for different situations but will also greatly help people in choosing the right one for ones’ businesses.  There isn’t any plan to identify as a comprehensive one for all needs and physical environments. So picking the right one for the right purpose is the target of most organizations have been looking for.

Source:  Hajmoosaei, A.; Kashfi, M.; Kailasam, P.; , “Comparison plan for data warehouse system architectures,” Data Mining and Intelligent Information Technology Applications (ICMiA), 2011 3rd International Conference on , vol., no., pp.290-293, 24-26 Oct. 2011

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