Author(s): Rajdeep Chowdhury, Bikramjit Pal, Saikat Ghosh

Email(s): dujon18@yahoo.co.in

DOI: Not Available

Address: Rajdeep Chowdhury*, Bikramjit Pal and Saikat Ghosh
Department of Computer Application, JIS College of Engineering Block ‘A’, Phase III, Kalyani, Nadia-741235, West Bengal, India
*Corresponding Author

Published In:   Volume - 3,      Issue - 3,     Year - 2011


ABSTRACT:
Data warehousing has evolved with every passing decade and it has come a long way from its inception and the modern era has made it an adequate part of pre-existing analytical methodologies. In the present status, data warehousing has evolved into a system which is capable of furnishing key performance metrics to high-level management, ensuring capability of analytical strength to middle-level management and aligning to the ability of providing corrective data to-and-fro back to low-level based on the basis of information derived from the analytical system. The data warehouse market is currently triggered by business-driven solutions focussing on domain specific challenges and its allied histrionics that have conjured up the very basic nuances of data warehousing. The present business idologies of the global village have cropped up innovative and tougher challenges for the data warehouse designers and architects to ensemble a bigger and much better innovation. Although, there are numerous methods available in the global market to cope up to this stiff challenges, but the evolutions have not made much of an impact in the global arena and the competitive market has prompted to venture into the unseen horizons over and over again. Data warehouses are designed to facilitate reporting and analysis. The said characteristic of the data warehouse mainly focuses on the data storage and acts much like a buffer to absorb continuous stock of data which gets processed via numerous iterative steps to evolve into information, awaited by all tiers of an organization for various decision-making processes. For over a decade, discussions and even controversies have lingered about which of the existing architectures is the best data warehouse architecture. The two “giants” of the data warehousing field, Bill Inmon and Ralph Kimball, are at the heart of disagreement. Inmon advocates the Hub & Spoke architecture (for example, the Corporate Information Factory), while Kimball promotes the data mart Bus architecture with conformed dimensions. There are other architecture alternatives, but these two options are fundamentally different approaches, and each has strong advocates via implementation.


Cite this article:
Rajdeep Chowdhury, Bikramjit Pal , Saikat Ghosh. Proposed Formula Based on Study of Correlation between Hub and Spoke Architecture and Bus Architecture in Data Warehouse Architecture, Based on Distinct Parameters. Research J. Science and Tech. 2011; 3(3): 154-157 .


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