Organizations that during the past years become accustomed to run its services on its on-premise solution, have increasingly to decide if they will in these days continue to operate their IT services in this way, or take advantage of new opportunities for cloud-based solution. However, the transition to this new technology, which entrusts their data into the hands of external companies, accompanied by a fear of security of their sensitive data. The main objective of this thesis is to propose a reference model that will assist organizations in their selection process of cloud service providers with respect to data security. In conclusion the quality and usefulness of this reference model is validated by knowledge and information, which are obtained during interviews with IT specialists.

The aim of the master thesis is to create an integrated view on the reporting for this less evident external user of accounting information. The thesis is split into two parts. The first part focuses on the actual data collection system MtS-ISL-SUD and its successor SDAT. Individual parts of the actual system are presented together with their functions. The possible means of submission of the reports are described and evaluated from different perspectives. The first part of the thesis also includes European requirements for the financial market supervision, on which the data collection is based. Second part of the thesis is devoted to the reports themselves. In three subchapters are presented the groups of reports with regards to the respective legislation. In the end the inner structure of the reports is presented on a chosen example.

The thesis deals with analysing and designing an effective dashboard. By way of introduction the topics of Business Intelligence, data storages and data quality are described. Then, an overview of analytical outputs is given and the process of their formation is outlined. The basic principles of an effective design of management reports are described, with emphasis laid on the end user. The thesis focuses on important factors of efficiency, such as applicability of transferred information and the form of their transfer. The practical part concentrates on the improvement of the efficiency of a particular dashboard. Besides the rules of a correct design, knowledge of cognitive psychology is also used for this purpose. Upon an analysis of deficiencies of an existing dashboard, proposed changes are incorporated. Changes resulting in more effective transfer of information via a dashboard are based on a theoretical basis of the previous section.

This thesis focuses on the information design in business intelligence. It combines cognitive psychology, graphic design and information design to equip the reader with information and skills to create effective reports and dashboards. The paper presents not only theory but also explains their principles. In the practical part of the theoretical knowledge is applied in practice on a sample dashboard that corrects the current solution imaginary company Alfa Kampeny. Although the work is primarily focused developer BI reports and dashboards, ideas contained therein apply to all those who have businesses are graphs and tables.

The topic of this master dissertation is data mining of customer data for marketing purposes within an enterprise. The information resulting from this process is then used to create targeted marketing campaigns. Nowadays, identifying and exploiting customer's needs is vital for any enterprise. With that in mind, the theoretical part of this dissertation is focused primarily on different methods of data analysis such as segmentation, profiling, customer scoring and determining customer value. A significant segment of this part focuses on web analysis, which studies customer's web browsing behaviour. The practical part of this dissertation is based on a case study of a specific e-shop. The case study identifies and solves problems of emailing realization. Solving these problems using Silverpop Engage brings new opportunities for emailing. The main goal of this dissertation is to show new opportunities of utilizing behavioural data for e-mailing campaigns execution.

Throughout last decades, knowledge discovery from databases as one of the information and communicaiton technologies' disciplines has developed into its current state being showed increasing interest not only by major business corporates. Presented diploma thesis deals with problematique of data mining while paying prime attention to its practical utilization within business environment. Thesis objective is to review possibilities of data mining applications and to decompose implementation techniques focusing on specific data mining methods and algorithms as well as adaptation of business processes. This objective is subject of theoretical part of thesis focusing on principles of data mining, knowledge discovery from databases process, data mining commonly used methods and algorithms and finally tasks typically implemented in this domain. Further objective consists in presenting data mining benefits on the model example that is being displayed in the practical part of the thesis. Besides created data mining models evalution, practical part contains also design of subsequent steps that would enable higher efficiency in some specific areas of given business. I believe previous point together with characterization of knowledge discovery in databases process to be considered as the most beneficial one's of the thesis.

Realised Stochastic Volatility model of Koopman and Scharth (2011) is applied to the five stocks listed on NYSE in this thesis. Aim of this thesis is to investigate the effect of speeding up the trade data processing by skipping the cleaning rule requiring the quote data. The framework of the Realised Stochastic Volatility model allows the realised measures to be biased estimates of the integrated volatility, which further supports this approach. The number of errors in recorded trades has decreased significantly during the past years. Different sample lengths were used to construct one day-ahead forecasts of realised measures to examine the forecast precision sensitivity to the rolling window length. Use of the longest window length does not lead to the lowest mean square error. The dominance of the Realised Stochastic Volatility model in terms of the lowest mean square errors of one day-ahead out-of-sample forecasts has been confirmed.

Ph.D. students are an integral part of the tertiary education system. Encouragement for doctoral programs and their students is very important because they are the ones who will participate in research projects in the future and they will contribute to society as a whole. The majority of scholarships for Ph.D. students comes from public sources. An important question to be asked is whether the scholarships are sufficient to finance Ph.D. studies and whether there are differences in the amount depending on gender, field of study or region. This thesis aims to answer these questions by applying statistical methods to the results of the survey DOKTORANDI 2014.

The thesis is focused on the development of JSF framework providing components for complex data visualizations. Its objective consists of the implementation of the API for creating JSF components rendering complex charts based on the JavaScript library C3.js and subsequent implementation of a set of chart components using this API. The contribution of this thesis is a library providing a tool for creating new JSF components based on C3.js together with a set of ready to use components. It begins with research of relevant JSF libraries, following with API analysis and design. Based on that is API implemented, in which a component set is then created. As a part of this work is a user guide, API reference guide and presentation web of implemented components.

This dissertation deals with the study of the use of virtual technologies for an analysis of operating characteristics of a machine. Operating characteristics of a machine are parameters that determine the usability of the machine to accomplish a certain task in addition to the specified time and under the certain conditions. These include parameters that can be changed based on customer requirements, for example, the table size and the highest spindle speed to the parameters influenced from the start of the machine design such as positioning accuracy, acceleration value in the axes or consumption. The first part sets out general requirements for visualization of information and these are subsequently verified experimentally in the chapter devoted to the time visualization protocol. This thesis presents the original experiments to determine the basic requirements for visualization of a measured quantity, in this case the feed rate. By verifying usability when displaying these properties on the underlying data showing machine position change, the four basic requirements for visual data processing using immerse virtual reality are validated. A deeper insight into the work with data will enable to analyse more complicated relations within a longer period, greater transparency and clearer outputs of analysis.