During last years information and communication technologies (ICT) are developing very dynamically and are penetrating into a lot of various business areas. Its perceiving is progressively changing from something rather sporadic, bringing a competitive advantage on the market, to absolute necessity determining existence or inexistence of certain enterprise among organizations able to compete.The paper maps actual state and evaluates develop needs in area of trade support by ICT devices in czech as well as european society in general, and this on the basis of accessible statistical evidences, publicised studies and various researches outcomes and other conducting sources. It notices problems or lacks in this area and it identifies trends in its solution.Some simple indicators and also complex indicator so-called “e-business index” are monitored for evaluating of actual state of ICT using in sphere of trading and also in order to possibility of successive identification of trends in this area. This summary indicator measures level of ICT using in certain enterprise, and integrates in itself, among others, some from mentioned simple statistics too. It is constructed from four main general subcategories, which are in more detailed way separated onwards.

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CHALUPOVÁ, N.,: Prediction of customer behaviour through datamining assets. Acta univ. agric. et silvic. Mendel. Brun., 2009, LVII, No. 3, pp. 43-54 Business managers accounting for commercial success or non-success of the organization have to gain knowledge needful for correct decision acceptance. These knowledge represent sophisticated information hidden in enterprise data. One possibility, how to extract mentioned knowledge from data, is to use so-called datamining assets. The paper deals with an application of chosen basic methods of knowledge discovering in da ta bases for area of customer-provider relation and it presents, how to avail acquired knowledge as basis of managerial decisions leading to improving of customer relationship management. It solves prediction, whose aim is, on the basis of some attributes of exploring objects, to predict future be ha viour of objects with these attributes. This way acquired knowledge, as the output of prediction, then can markedly help competent enterprise manager with planning of marketing strategies, for example socalled cross-selling and up-selling. The contribution describes a whole operation of available data processing: from its purifying, over its preparation for mining task, to self processing by the help of SAS Enterprise Miner tool. Regression analysis, neural network and decision tree, whose principles are briefl y explained in this paper too, were used for knowledge mining. The estimation of customer behaviour was tested by two mining task varying in attribute using and in categories number of one of predicive attributes. The results of these two tasks are confronted by the help of prediction fruitfulness charts.knowledge discovery in databases, datamining, prediction, customer, decision process, control Chce-li fi rma obstát v současném konkurenčním prostředí trhu, je nezbytné, aby sledovala chování svých zákazníků. Za obchodní úspěch či neúspěch organizace odpovídají podnikoví manažeři, a ti proto musí získávat znalosti potřebné pro přijetí správ-ného rozhodnutí. Tyto znalosti představují sofi stikované informace ukryté v datech, která má podnik k dispozici. Novotný, Pour a Slánský (2005) uvádějí, že objem dat se v podniku zdvojnásobí v průměru každých pět let, což znamená, že v současné době již není problém data získat a uchovat, ale efektivně je zpracovat a využít jejich potenciál.Možností, jak zmiňované znalosti z dat získat, je využít prostředků tzv. dataminingu. Tento obor se zabývá otázkami, jak nalézt v datech souvislosti, které nejsou přímo zřejmé, a které napomáhají lépe porozumět fi remním procesům. Jednou z význam-ných úloh dataminingu je predikce, jejímž cílem je na základě určitých vlastností zkoumaných objektů předpovědět budoucí chování objektů s tě-mito vlastnostmi. Výsledný výstup (předpověď) pak může výrazně napomoci při tzv. křížovém prodejisnahy, jejichž účelem je navýšit objednávku zákaz-níka doporučením jiných produktů nabízených společností (Clemente, 2004) a následném prodeji -aktivity, jejichž cílem je nabídnout zákaz...

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The contribution deals with design of customer–provider relationship monitoring system solution with regard to needs of business managers and analytics and to possibilities of contemporaneous information and communication technologies.The attention is followed to targeted modelling, what brings possibilities of acquisition of bigger overview about things taking place in the relation. In consequence it describes the functionality of analytical systems producing these very strategically valuable models – to so-called business intelligence tools. Onward it deals with modern technologies conductive to above mentioned system implementation – with Ajax concept and with some XML applications: PMML for analytical models manipulation, XSLT for XML data transformations to various formats, SVG for representing pictures of statistical graphs etc. and MathML for description of mathematical formulas created in analytical systems.Following these basis it suggests technological solution of some parts of client–provider relationship watching and evaluating system and it discusses its potential advantages and problems, which can occur.