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This diploma thesis concerns with features and abilities of chosen software tools for data mining. An important part is the selection and evaluation of each criteria by which the comparison of tools is done. The basic issues of data mining and machine learning are determined here. The comparison criteria are chosen with consideration of the necessary operations that are required to realize the whole process of data mining. The criteria are evaluated on the same level of importance, without weighting. The most widely used algorithms for data mining are chosen for the comparison of time and memory demandingness. The result is the description of selected tools based on the comparison criteria and evaluation of these criteria. The comparison results must be understood with respect of testing data, chosen hardware, and the fact that no weighting was used.

In this work we propose a solution that would help automate the part of knowledge discovery in databases. Domain knowledge has an important role in the automation process which is necessary to include into the proposed program for data preparation. In the introduction to this work, we focus on the theoretical basis of knowledge discovery of databases with an emphasis on domain knowledge. Next, we focus on the basic principles of data pre-processing and scripting language LMCL that could be part of the design of the newly established applications for automated data preparation. Subsequently, we will deal with application design for data pre-processing, which will be verified on the data the House of Commons.

This work deals with the issue of Data and Information Quality. It critically assesses the current state of knowledge within tvarious methods used for Data Quality Assessment and Data (Information) Quality improvement. It proposes new principles where this critical assessment revealed some gaps. The main idea of this work is the concept of Data and Information Quality Management across the entire universe of data. This universe represents all data sources which respective subject comes into contact with and which are used under its existing or planned processes. For all these data sources this approach considers setting the consistent set of rules, policies and principles with respect to current and potential benefits of these resources and also taking into account the potential risks of their use. An imaginary red thread that runs through the text, the importance of additional knowledge within a process of Data (Information) Quality Management. The introduction of a knowledge base oriented to support the Data (Information) Quality Management (QKB) is therefore one of the fundamental principles of the author proposed a set of best

The mortality is historically one of the most important demographic indicator and definitely reflects the maturity of each country. The objective of this diploma thesis is the comparison of mortality rates in analyzed countries around the world over time and among each other using the principle component analysis that allows assessing data different way. The big advantage of this method is minimal loss of information and quite understandable interpretation of mortality in each country. This thesis offers several interesting graphical outputs, that for example confirm higher mortality rate in Eastern European countries compared to Western European countries and show that Czech republic is country where mortality has fallen most in context of post-communist countries between 1990 and 2010. Source of the data is Human Mortality Database and all data were processed in statistical tool SPSS.

The goal of this thesis is to optimize the existing energy consumption monitoring system and expand the presentation options for the measured data in a way that would be suitable for large volume of data and a long period of time. Optimization concerns especially data processing and data presentation.

Bezpečnost a zachování důvěrnosti dat uložených s využitím veřejných cloudových služeb je dnes velmi aktuální téma. V této práci se, na rozdíl od tradičního šifrování, zabýváme možností využití dělení dat k zabezpečení citlivých dat. Cílem práce je implementovat a porovnat dva již publikované protokoly pro násobení matic využívající dva rozdílné přístupy dělení dat. Na základě jejich vlastností byla navržena originální varianta, která na rozdíl od původních protokolů zohledňuje i případ, kdy poskytovatelé cloudových slu- žeb tajně spolupracují. Všechny tyto protokoly byly naimplementovány za použití plat- formy Java a veřejných cloudových služeb. Na závěr byla změřena výkonnostní náročnost a zhodnoceny požadavky na úložiště.

The task of the thesis is a theoretical analysis and description of the use of company data. Emphasis is placed on the system analysis of the problem. The specific production process and the data available from it are evaluated, which help to find a technical and economic evaluation.

The diploma thesis is focused on the design of a backup system to increase the efficiency of working with stored data and increase the security of stored data. The analysis of the current state describes the company itself and also the backup system using the audit portal Zefis.cz. The following part describes the design of a new backup system that focuses on complexity using the cloud, magnetic tapes, and high server availability.

This paper explores the potential of process data distribution in real time using the RTP protocol. Firstly, there is an evaluation of existing protocols that are used for this purpose. Secondly, there is a description of the trio of protocols RTP, RTCP, and RTSP, explained their functions and explored possibilities for their expansion. On the basis of this acquired knowledge, problems which may occur with the distribution of process data by means of RTP are identified and their possible solutions are proposed. To demonstrate the data distribution via RTP, the application, that collects GPS position from the PDA and then provides clients with them, has been designed and implemented. Clients can display these data on the map.