Business Intelligence Architecture for Corruption Measurement: Data Warehouse driven Business Intelligence Model for better analysis of corruption data

Mohammad Aminul Hoque Chowdhury

ISBN 10: 3659905070 / ISBN 13: 9783659905070

Editore: LAP LAMBERT Academic Publishing, 2016

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104 pages. 8.66x5.91x0.24 inches. In Stock.

Codice articolo 3659905070

Dati bibliografici

• Titolo: Business Intelligence Architecture for Corruption Measurement: Data Warehouse driven Business Intelligence Model for better analysis of corruption data
• Editore: LAP LAMBERT Academic Publishing
• Data di pubblicazione: 2016
• Lingua: Inglese
• ISBN 10: 3659905070
• ISBN 13: 9783659905070
• Rilegatura: Paperback
• Condizione: Brand New

Descrizione articolo

Riassunto

This book is very useful to develop a data warehouse and business intelligence in a simple way for development project information management and data visualization. Readers can get latest data warehouse development idea and how it can be fit for development project monitoring and how it can link to Sustainable Development Goals (SDGs). Author tested his Data Warehouse driven Business Intelligence model for the Victim of Corruption Measurement Research Data Analysis and he found many interesting gaps. This project demonstrates that available Business Intelligence software can be applied to existing development data-sets to give socio-economic policy makers tools by which user can explore data to give new insights. The research allowed analysis of trends to be drilled by geographic region, gender, economic status etc. This research may be a distinct addition to strengthening the movement fighting the negative effects of bribery and corrupt practices.

L'autore

Mr Amin Chowdhury was born in Brahmanbaria of Bangladesh. He conducted research at the heffield Hallam University, UK on Business Intelligence for Development Sector and later he extended that research at the University of Cambridge. He is expert in Data Warehouse driven Business Intelligence. Now He worked for USAID ACME, TIB, and UNICEF.