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Proposed Business Principles Governing Enterprise Data Warehouse Design:Conceptual Framework with Enhancement of Knowledge Infrastructure via Context Model


Affiliations
1 Department of Computer Application, JIS College of Engineering, Block ‘A’, Phase III, Kalyani, Nadia–741235, West Bengal, India
2 Department of Engineering and Technological Studies, University of Kalyani, Kalyani, Nadia–741235, West Bengal, India
     

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A Data Warehouse can quite easily become a dilemma if it is not designed, implemented and maintained specifically and properly. Keeping this in mind, the discussion about the newly proposed business principles, which are believed to help a business start and keep the data warehouse design and implementation on the road to achieve desired results, have been compiled. Inclusion of issues from both the business perspective as well as the perspective of information technology scenario has made a major difference and a significant impact to the business intellectuals.

The conceptual framework has been devised with the notion of enhancing the knowledge infrastructure, thereby ensuring better results on the totality. The conceptual framework has been pictorially demonstrated in the Context Model section, with the view of establishing enhancement of knowledge infrastructure through the unfathomable podium of expressing the new and innovative seven proposed business principles formulated.

The proposed principles amalgamated with the existing principles will aid any designer with suitable referent points to come up with the goods for his/her enterprise.

All the proposed principles have been detailed in the Implementation via Proposed Principles section and can be mostly incorporated in the modern enterprises.


Keywords

Data Warehouse, Business Principles, Technological Versatility, Inter-Organizational Synchronization and Inter-Personal Rapport, Transitive Diversification, Intrinsic Cause Effect Analysis, Coherent Feedback and Survey Mechanism, EP, PP, Context Model.
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  • Proposed Business Principles Governing Enterprise Data Warehouse Design:Conceptual Framework with Enhancement of Knowledge Infrastructure via Context Model

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Authors

Rajdeep Chowdhury
Department of Computer Application, JIS College of Engineering, Block ‘A’, Phase III, Kalyani, Nadia–741235, West Bengal, India
Bikramjit Pal
Department of Computer Application, JIS College of Engineering, Block ‘A’, Phase III, Kalyani, Nadia–741235, West Bengal, India
Mallika De
Department of Engineering and Technological Studies, University of Kalyani, Kalyani, Nadia–741235, West Bengal, India

Abstract


A Data Warehouse can quite easily become a dilemma if it is not designed, implemented and maintained specifically and properly. Keeping this in mind, the discussion about the newly proposed business principles, which are believed to help a business start and keep the data warehouse design and implementation on the road to achieve desired results, have been compiled. Inclusion of issues from both the business perspective as well as the perspective of information technology scenario has made a major difference and a significant impact to the business intellectuals.

The conceptual framework has been devised with the notion of enhancing the knowledge infrastructure, thereby ensuring better results on the totality. The conceptual framework has been pictorially demonstrated in the Context Model section, with the view of establishing enhancement of knowledge infrastructure through the unfathomable podium of expressing the new and innovative seven proposed business principles formulated.

The proposed principles amalgamated with the existing principles will aid any designer with suitable referent points to come up with the goods for his/her enterprise.

All the proposed principles have been detailed in the Implementation via Proposed Principles section and can be mostly incorporated in the modern enterprises.


Keywords


Data Warehouse, Business Principles, Technological Versatility, Inter-Organizational Synchronization and Inter-Personal Rapport, Transitive Diversification, Intrinsic Cause Effect Analysis, Coherent Feedback and Survey Mechanism, EP, PP, Context Model.