Business Intelligence
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Business Intelligence, according to Gartner Group, is the process of gathering, exploring, interpretation and data analysis, leading to enhancing and rationalization of decision making processes.
The basic fields of development for Business Intelligence are:
- Statistics and Econometrics: statistical theory of pattern recognition in images, taximetrics, statistical reasoning and prognosis.
- Operational Research * linear programming, decision theory, game theory
- Artificial Intelligence * heuristic search strategies, computer learning, expert systems, genetic algorithms and neural networks.
- Databases * data modeling, query language, database optimization.
Three main technologies used in Business Intelligence are grouped in following:
- OLAP (online analytical processing) tools: software enabling the multidimensional analysis of business information through integration, aggregation and visualization (automated and preconfigured charts, tables or diagrams) of data.
- Data Mining tools: algorithms enabling for automated analysis of large databases, using statistics and econometrics, as well as machine learning (in order to analyze data not only with use of quantitative variables, but also with descriptive or text variables).
- Knowledge Management tools: systems and organizational methods enabling for gathering, indexing, categorizing, research and analysis of text documents.
Business Intelligence systems are used primarily as a support in management of two groups of problems.
The first one are governance tasks, connected with overseeing day-to-day operations of staff.
The second one is analysis of well-structured problems, which can described as decisions that can be programmed as an algorithm. Those problems should have normative, standardized procedures governing all the decisions to be taken during the course of
Business Intelligence is not used on a regular basis as a solution to ill-structured problems, which can be described as problem new to a particular organization or experimental projects. Examples for ill-structured problems are: decision on entering a new market or development of a prototype of a new, ground-breaking service or product.
See also:
Bibliografia
- Luhn, H. P. (1958). A business intelligence system. IBM Journal of Research and Development, 2(4), 314-319.
Author: Anna Morawiec
