Always-On Enterprise Information Systems for Business by Nijaz Bajgoric

By Nijaz Bajgoric

So that it will remain aggressive, smooth companies have to undertake an company info method or an built-in IT platform that operates on an always-on foundation that allows you to stay resilient, non-stop, operational, adaptive, and responsive during this more and more aggressive and altering company setting. Always-On company info platforms for enterprise Continuance: applied sciences for trustworthy and Scalable Operations presents an in-depth and scientifically-based research of always-on firm info structures. invaluable to academicians, researchers, and practitioners, this complicated book identifies methodological frameworks for designing and constructing effective structures and powerful suggestions for always-on implementation.

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Ibidem. Standish Group in their 2004 The Chaos Report, claimed that only 29 percent of all IT projects succeeded while the remainder were either challenged or failed, source: (ITGI, 2006). A 2002 Gartner publication reported that 20 percent of all expenditure on IT is wasted, representing, on a global basis, annual value destruction of US $600 billion. Source (Gartner, 2002). For example, Nike reportedly lost more than US $200 million through difficulties experienced in implementing its supply chain software.

SEMMA covers the following steps: • • • • • Sampling Exploring (revealing data quality related problems) Manipulating (data quality improvement) Modeling Assessment. Many authors have written about data mining theory and practice, amongst other Berry (2002), Linoff and Berry (1997), Han and Kamber (2004), Edelstein (1999), Adriaans and Zantige (2002) and Kantardzic (2002). Business intelligence projects are time and resource consuming ones with several risks and challenges. Next session details risks and business continuity related issues of business intelligence solutions.

Data remains in separate systems in this approach. Semantic web offers another way for data integration, because it can be used to wrap data into repositories. Organizational assets in data warehouse are utilized by several business intelligence solutions, like reporting, OLAP and data mining. OLAP (online analytical processing) provide methods for managers to conduct analysis on data, slice and dice data, meanwhile visualisation of the steps and the results is supported. Databases customized for OLAP employ a multidimensional data model, allowing for complex analytical and ad-hoc queries.

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