Acta Univ. Agric. Silvic. Mendelianae Brun. 2005, 53, 85-92

https://doi.org/10.11118/actaun200553060085
Published online 2014-12-20

Business Intelligence and competition ability of enterprise

Vladimír Konečný, Ivana Rábová

Ústav informatiky, Mendelova zemědělská a lesnická univerzita v Brně, Zemědělská 1, 613 00 Brno, Česká republika

As far as the current state of the information and communication technologies usage is concerned, the information systems of the companies cover the major part of the transaction processes and the large amount of the processes at the level of the tactical decision-making.
Intensive implementation of the information technologies in many areas of the human activities cause gathering of the large amount of the data. The volume of the internal and external databases grows rapidly and the problem is to take advantage of the data they contain. But the problem is not only the growing volume of the databases but also the different and database structures. To get the new information from the large and incompatible database sources is possible but very inefficient. A manager often needs the information very fast to achieve competitive advantage and to solve problems at the level of strategic decision-making.
Another problem is the fact that the databases often contain information that is hidden there and there is no way known how to get this information out of the database. In this case, the user needs at least suitable tools in order to perform experiments and to explore and identify patterns and relationships in the data.
The transformation process of the data to information and to knowledge that is used in the process of decision-making is called Business Intelligence. Modern database tools offer wide support for building the data warehouse, OLAP analysis and data mining.
Our contribution focuses on the application of one of the data mining techniques such as neural networks and artificial intelligence. The application of those methods will be based on the assessment of the food quality and composing of the corresponding trend indicator.

References

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