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Theory and Practice in Business Intelligence

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  • Muntean, Mihaela

Abstract

The debate is developed based on the following considerations: 1 - Business Intelligence (BI) is unanimous considered the art of gaining business advantage from data; therefore BI systems and infrastructures must integrate disparate data sources into a single coherent framework for real-time reporting and detailed analysis within the extended enterprise; 2 - Business Intelligence can be described as a value proposition that helps organizations in their decision-making processes; 3 – the Business Intelligence Value Chain represents a „From DATA To PROFIT“ approach and is recommended to ground any performance management program. Different aspects, including theoretical considerations and practice examples, regarding location intelligence, mobile BI, cloud-based BI, social BI and collaborative Business Intelligence will be treated, pointing out some of the author’s contributions. Nowadays, organizations have adopted more prudent policies requiring a financial justification for nearly every IT initiative, including Business Intelligence system implementations. A business-driven methodology is recommended in any BI project management approach, project scoping and planning being vital for the project success. A business-driven approach of a BI project implementation starts with a feasibility study. The decision-making process for large projects is very complicated, and will not be subject of this paper. Having in mind a middle-sized BI project, a feasibility study based on the Monte Carlo simulation method will be conducted.

Suggested Citation

  • Muntean, Mihaela, 2012. "Theory and Practice in Business Intelligence," MPRA Paper 41359, University Library of Munich, Germany, revised 15 Sep 2012.
    • Handle: RePEc:pra:mprapa:41359
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    File URL: https://mpra.ub.uni-muenchen.de/41359/1/MPRA_paper_41359.pdf
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    References listed on IDEAS

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    1. Muntean, Mihaela & Mircea, Gabriela & Bazavan, Sandra, 2012. "QR Codes Usage Approach In The Virtualized Consumption," MPRA Paper 41141, University Library of Munich, Germany, revised 27 Apr 2012.
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    Cited by:

    1. Teodora Vătuiu & Mioara Udrică & Naiana Tarcă, 2013. "Cloud Computing Technology - Optimal Solution for Efficient Use of Business Intelligence and Enterprise Resource Planning Applications," Journal of Knowledge Management, Economics and Information Technology, ScientificPapers.org, vol. 3(6), pages 1-28, December.
    2. Mihaela Muntean, 2018. "Business Intelligence Issues for Sustainability Projects," Sustainability, MDPI, vol. 10(2), pages 1-10, January.

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    1. Teodora Vătuiu & Mioara Udrică & Naiana Tarcă, 2013. "Cloud Computing Technology - Optimal Solution for Efficient Use of Business Intelligence and Enterprise Resource Planning Applications," Journal of Knowledge Management, Economics and Information Technology, ScientificPapers.org, vol. 3(6), pages 1-28, December.

    More about this item

    Keywords

    Business Intelligence (BI); BI value chain; BI project; Location Intelligence; Social BI; Mobile BI; Cloud BI; Collaborative BI;
    All these keywords.

    JEL classification:

    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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