Preface. Acknowledgments. About the Authors. Part I Introduction to Business Intelligence. Chapter 1 Business Intelligence and Its Impacts. Chapter 2 Business Intelligence Capabilities. Part II Technologies Enabling Business Intelligence. Chapter 3 Technologies Enabling Organizational Memory. Chapter 4 Technologies Enabling Information Integration. Chapter 5 Technologies Enabling Insights and Decisions. Chapter 6 Technologies Enabling Presentation. Part III Management and Future of BusinessIntelligence. Chapter 7 Business Intelligence Tools and Vendors. Chapter 8 Development of Business Intelligence. Chapter 9 Management of Business Intelligence. Chapter 10 The Future of Business Intelligence.
See Full PDF See Full PDFAnalele Stiintifice ale Universitatii
Download Free PDF View PDF
International Management Review
Download Free PDF View PDF
Business intelligence (BI) is a broad category of applications, technologies, and processes for gathering, storing, accessing, and analyzing data to help business users make better decisions. This tutorial discusses some of the early, landmark contributions to BI; describes a comprehensive, generic BI environment; and discusses four important BI trends: scalability, pervasive BI, operational BI, and the BI based organization. It also identifies BI resources that are available for faculty and students.
Download Free PDF View PDF
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.
Download Free PDF View PDF
