This diploma thesis deals with the possibility of presentation data in business intelligence (BI) applications. The aim is to develop a methodology for reporting and data visualization using Microsoft SQL Server 2008 Business Intelligence Development Studio and Microsoft Excel 2010. Evaluate and identify opportunities for data display using the perception of information at a subconscious level in the above mentioned tools. Identify market trends from the perspective of business intelligence data visualization. In the first part thesis focuses on the analysis of the current BI market with regard to trends in data visualization. In the following part options of perceptions on a subconscious level are examined, which are then reflected in the establishment of a methodology reporting. Similarly, it is investigated the human perception of color. Presented are appropriate and inappropriate data visualization forms, at the most commonly used graphic forms. The work describes a method to ensure that the data will not be displayed tendentiously or distorted. My contribution is creating a reporting methodology that respects the life cycle of the report, as well as a logical follow-up steps to project management.

At the very beginning of the diploma thesis, we introduce the reader to the issues of BI and controlling of manufacturing companies. Subsequently, we perform an analysis and evaluation of the current state of the selected manufacturing company in terms of variations in production. Then we use MSSQL server and SSAS to create a controlling model. The company will be able to unambiguously and quickly identify weaknesses in production and quickly eliminate them. Finally, we evaluate the real benefits of this project for the company.

This Diploma Thesis deals with analysis of the current processes in small software company. On the basis of the weakness evaluation, the new extensions of the information system are designed. The first extension is new module for on-line sale and cashless on-line payment. The second one is integration of Business Intelligence tools to help streamline marketing strategies of this company.

This master thesis deals with the software support of one Financial and Property Analysis of Municipalities (FAMA). The co-author of this method is Doctor Petr Toth from the Institute of Public Administration and Regional Development at University of Economics in Prague. The method is supported by Microsoft Access database application and two C++ applications ArisDestiller and Prognoza at present time. The aim of this thesis is to evaluate the present software support of Financial and Property Analysis and implement an alternative solution based on Business Intelligence tools. Chosen part of analysis is implemented in the pilot project using Microsoft SQL Server 2005 environment. The thesis focuses mainly on using integration tools for XML data. The contribution of the thesis is to implement data warehouse, which uses the municipalities'annual bills in XML format from the database of Ministry of Finance of the Czech Republic. The Financial and Property Analysis method and the current software support are discussed in the first half of this thesis. The other half of the work is dedicated to the Business Intelligence pilot project. Both means of software support are reviewed and compared from various perspectives in the conclusion.

This master's thesis is focused on knowledge discovery from databases, especially on methods of mining sequential patterns. Individual methods of mining sequential patterns are described in detail. Further, this work deals with extending the platform Microsoft SQL Server Analysis Services of new mining algorithms. In the practical part of this thesis, plugins for mining sequential patterns are implemented into MS SQL Server. In the last part, these algorithms are compared on different data sets.

This thesis deals with association rules mining over data warehouses. In the first part the reader will be familiarized with terms like knowledge discovery in databases and data mining. The following part of the work deals with data warehouses. Further the association analysis, the association rules, their types and mining possibilities are described. The architecture of Microsoft SQL Server and its tools for working with data warehouses are presented. The rest of the thesis includes description and analysis of the Star-miner algorithm, design, implementation and testing of the application.