Theory and Practice in Business Intelligence

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.

Business Intelligence Issues for Sustainability Projects

“…Previous research by the author [6,20] has been focused on some theory and practice issues in business intelligence, with the BI value chain being introduced in terms of a value proposition [26]. Raw data is extracted from different data sources, further integrated into a multi-dimensional data model, which is nowadays usually stored in an "in-memory database".…”

Small and medium enterprise business solutions using data visualization

“…Forrester defined BI as a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information used to enable more effective strategic, tactical and operational insights and decision-making that can put a company ahead of its competitors [10]. In a more recent attempt, Muntean [11] considered the BI term to cover the art of picking up business advantage from data by coordinating divergent information sources into a solitary framework for real-time revealing and detailed investigation inside the broadened enterprise. Although Dresner's original definition of BI [7], as well as more recent definitions from analysts like Forrester [10], are broad in scope, most practitioners associate with the term a narrow set of capabilities, such as extraction, transformation, and loading (ETL); data warehousing; on-line analytical processing (OLAP); and reporting [12].…”