This thesis deals with the MySQL database synchronization. The goal of this work was to get acquainted with database synchronization in a broader context, to choose the appropriate tools for real usage, and them to implement, evaluate and analyze these tools. From these techniques was selected MySQL replication technology that solves the synchronization task of distributed evidence database system of health implantable devices in the best way. The replication was implemented on this database system and after the testing was used in the company Timplant Ltd.

Methodology and issues of data transformation and its information value estimation during the integration of the heterogenous information sources PhDr. Ivan BARTOŠ Abstract This study focuses mainly on the data and information transformation issue. This topic is currently critical in several scientific and commercial areas. Information value, information quality and the quality of the source data differs between the various systems. This is not only due to the different topologies of the information sources but also because of its different understanding and a manner of storing the information describing the entity of the enterprise. Such information systems, respectively database systems in the scope of the thesis, could perform well as the stand alone systems. The issue appears in the moment when such heterogeneous systems are required to be integrated and the information shall be migrated between each other. The thesis is logically divided into four major parts based on these issues. The first part describes the methods that can be used to classify the data quality of the source system (the one to be integrated) from which the information can be extracted. Based on assumption of the common lack of project and system documentation hereby introduced methods can be used for such qualification even when the...

This thesis deals with the areas of enterprise data quality, data integrity and data consolidation from the perspective of Business Intelligence (BI), which is currently experiencing significant growth. The aim of this thesis is to provide a comprehensive view of the data quality in terms of BI, to analyze problems in the area of data quality control and to propose options to address them. Moreover, the thesis aims to analyze and assess the features of specialized software tools for data quality. Last but not least aim of this thesis is to identify the critical success factors in the field of data quality in CRM and BI projects. The thesis is divided into two parts. The first (theoretical) part deals with data quality, data integrity and consolidation of data in relation to BI trying to identify key issues, which are related to these areas. The second (practical) part of the thesis deals at first with the features of software tools for data quality and offers their fundamental summary as well as the tools breakdown. This part also provides basic comparison of the few selected software products specialized at the corporate data quality assurance. The practical part hereafter describes addressing the data quality within the specific BI/CRM project conducted by Clever Decision Ltd. This thesis is intended primarily for BI and data quality experts, as well as the others who are interested in these disciplines. The main contribution of this thesis is that it provides comprehensive view not only of data quality itself, but also deals with the issues that are directly related to the corporate data quality assurance. This thesis can serve as a sort of guidance for one of the first implementation phases in the BI projects, which deals with the data integration, data consolidation and solving problems in the area of data quality.

This work deals with the data migration during the process of mergers and acquisitions. The first, theoretical part, defines the general terms concerning mergers and acquisitions, further mentions motives that may lead to it, and the basic stages of the implementation process of mergers and acquisitions. This section also presents brief information on selected methodologies of project management, of which principles are used in the next part, dealing with data migration projects. The aim of this work is to develop a methodology for project management of data migration in mergers and acquisitions process, which may serve as a guide for merging companies and data migration teams. In the methodology there are specified activities and defined procedures to be followed in the various stages of the project life cycle. To each activity the way and necessary prerequisites for carrying out are specified. The methodology also describes common problems with which the data migration project in carrying out the action may be faced and which could threaten the success of the project or its part. For each potential problem a possible way to eliminate it is added, or solutions.

This thesis focuses on solving problems related to searching of relevant data on the internet. In text is presented possible solution in form of application capable of automated extraction and aggregation of data from web and their presentation, based on input key words. For this purpouse there were studied and discribed possibilities of automated extraction from three chosen data types, mainly used as data storages on the internet. Furthermore it focuses on ways of data mining from social networks. As a result it pressents planning, implementation, realization and testing of created appliation which can easily find, display and let user easy access searched informations.

This MSc Project deals with the system of Knowledge Discovery in Databases. It is a client application which uses the Oracle Data Mining Server's 10.g Release 2 (10.2) services. The application is implemented in Java, the graphical user interface is built on the NetBeans Rich Client Platform. The theoretical part introduces the Knowledge Discovery in Databases, while the practical part describes functionality of the original system, it's deficiencies, documents sollutions of theese deficiencies and there are proposed improvements for further development. The goal of this project is to modify the system to increase the application usability.

This master thesis is focused on volumetric data rendering and on highlighting and visualization of the selected cells of the model organisms. These data are captured by a confocal deconvolution microscope. Input data form one large volumetric block containing separate slices. This data block is rendered by an applicable method and then are identified and visualized the cells marked by the GFP (Green Fluorescent Protein) process or by chlorophyle fluorescency. The principal aim of this work is to find out the preferably optimal effective method enabling this highlighting, most preferably working without a manual check. Due to the data structure, this ambition seems hardly realizable, so it suffices to find out a manual working method. The last step is to embed the results of this work into FluorCam application, the confocal deconvolution microscope data visualizer.

The master thesis present the possibilities of processing of electrochemical data from a group of four electrodes with non-selective response (simple sensor array) for electrochemical analysis with potential application of the results achieved in the construction of the sensor field type "electronic tongue". This simple system was applied to the sample simulating the food product. Electrochemical data were processed through mathematical operations such as Gaussian approximation, deconvolution or using basic mathematical operations.

This diploma thesis deals with the data quality management. There are many tools and methodologies to support the data quality management even in Czech market but they are all only for large companies. Small and middle companies can't afford them because of high cost. The first goal of this thesis is to summarize principles of the methodologies and then on the base of the methodologies to suggest more simple methodology for small and middle companies. In the second part of thesis is created and adapted the methodology for a specific company. The first step is to choose the data area of interest in the company. Because of impossibility to buy a software tool to clean data, there are defined relatively simple rules which are base source to create cleaning scripts in SQL language. The scripts are used for automatic data cleaning. On the base of next analyze is decided what data should be cleaned manually. In the next step are described recommendations how to remove duplicities from the database. There is used a functionality of the company's production system. The last step of the methodology is to create a control mechanism which have to keep the required data quality in future. At the end of thesis is made a data research in four data sources. All these sources are from companies using the same production system. The reason of research is to present the overview of data quality and to help with decision about cleaning data in the companies also.

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