The aim of this thesis is analysis of data of the Czech Statistical Office concerning foreign trade. At first, reader familiarize with Business Intelligence and data warehousing. Further, OLAP analysis and data mining basics are explained. In next parts the thesis deal with describing and analysis of data of foreign trade by the help of OLAP technology and data mining in MS SQL Server including selected analytical tasks implementation.

The main aim of this diploma thesis is to propose for changes in the company information system. Document content is focuse on analyse, implementation and using data warehouse and usage advance to optimaze methods for achievement added value to users. The first part of this thesis is focused on choice of suitable concept of data warehouse, implementation and possible problems. In the second part, I compare assets of this system with costs for development and administration.

The thesis is focused on issues of information systems, evaluates advantages, disadvantages and possible risk coming from implementation of IS. In theoretical part are the main issue ERP systems, its history and modern trends in this field. It aims also on the analytical tools business intelligence, which are helpful in the decision-making process creating future strategy of the company. In practical part the information system of Kermi will be evaluated by using analytical methods HOS 8 and Zefis. With the help of both tools the problematic part of the information system will be found and then aim of this thesis will be elimination of these problems.

I have chosen this topic of my paper, because I have been working in Divadlo Husa na provázku as a network administrator. The every day problems I have been contending with should be eliminated by this project as well as it can bring some new pleasant function in whole computer infrastructure. In theoretical part of my paper I will engage in information systems in general and it’s analyse. In a practical part of my paper I will use HOS 8 analyse for evaluation of current IS. After this analyse some variation of improvement will be introduced. In final part of this paper will be the financial calculation of suggested solutions included.

At the beginning, the project describes basics and utilization of data warehousing and OLAP techniques and operations used within the data warehouses. Then follows a description of one of the commercial OLAP client - based on the features of this product the requirement analysis of the freeware OLAP cube client displayer is desribed - choosing the functionality to be implemented in the client. Using the requirement analysis the structural design of the application (including UML diagrams) is made. The best solution from compared libraries, frameworks and development environments is chosen for the design. Next chapter is about implementation and tools and frameworks used in implemetation. At the end the thesis clasifies the reached results and options for further improvement.

The thesis generally describes matters of data warehouses and knowledge discovery in databases. Then it focuses on the meteorological databases and their problems. The practical part of thesis describes design methods for data mining project, NOAA Global Surface Summary of the Day (GSOD), which is then implemented in two different ways using the Pentaho tools. Finally, an evaluation and comparison of these two approaches.

The purpose of this work is in analytical tool supporting manager decision making. The goal was to develop a reporting system which simplifies company customer's orientation in key performance indicators. As implementation environment has been used .NET Framework 3.5 with C\# language and database server Microsoft SQL 2008 with Analysis Services extension, for web interface has been used ASP.NET.

The amount of data accumulated by organizations have grown significantly during the last couple of years, increasing the importance of data quality. Ensuring data quality for large amounts of data is a complicated task, but crucial to subsequent analysis. This study investigates how to maintain and improve data quality in a data warehouse. A case study of the errors in a data warehouse was conducted at the Swedish company Kaplan, and resulted in guiding principles on how to improve the data quality. The investigation was done by manually comparing data from the source systems to the data integrated in the data warehouse and applying a quality framework based on semiotic theory to identify errors. The three main guiding principles given are (1) to implement a standardized format for the source data, (2) to implement a check prior to integration where the source data are reviewed and corrected if necessary, and (3) to create and implement specific database integrity rules. Further work is encouraged on establishing a guide for the framework on how to best perform a manual approach for comparing data, and quality assurance of source data. / Mängden data som ackumulerats av organisationer har ökat betydligt under de senaste åren, vilket har ökat betydelsen för datakvalitet. Att säkerställa datakvalitet för stora mängder data är en komplicerad uppgift, men avgörande för efterföljande analys. Denna studie undersöker hur man underhåller och förbättrar datakvaliteten i ett datalager. En fallstudie av fel i ett datalager på det svenska företaget Kaplan genomfördes och resulterade i riktlinjer för hur datakvaliteten kan förbättras. Undersökningen gjordes genom att manuellt jämföra data från källsystemen med datat integrerat i datalagret och genom att tillämpa ett kvalitetsramverk grundat på semiotisk teori för att kunna identifiera fel. De tre huvudsakliga riktlinjerna som gavs är att (1) implementera ett standardiserat format för källdatat, (2) genomföra en kontroll före integration där källdatat granskas och korrigeras vid behov, och (3) att skapa och implementera specifika databasintegritetsregler. Vidare forskning uppmuntras för att skapa en guide till ramverket om hur man bäst jämför data genom en manuell undersökning, och kvalitetssäkring av källdata.

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Os resíduos urbanos descartados de forma irregular constituem um problema sério, principalmente nas grandes cidades, causando entupimento de bueiros e drenagem com conseqüentes inundações, sujeira e transmissão de doenças tais como leptospirose e dengue além de ser um estorvo para o trânsito e acarretarem gastos para a Prefeitura. Por outro lado, reciclar este material é uma fonte de receitas e um gerador de empregos. A Geovisualização Analítica pode ser de grande auxílio para a análise desse problema complexo e para a tomada de decisão. Com essa motivação, a presente dissertação procura fornecer uma visão geral sobre o estado da arte quanto a conceitos e pesquisas em Geovisualização (GVis) e Processamento Analítico (OLAP e SOLAP). Apresenta também processos, metodologias e tecnologias que foram utilizadas no desenvolvimento de um protótipo de um sistema analítico de informações aplicado à área de gestão da coleta seletiva de resíduos sólidos recicláveis em ambiente urbano. Este protótipo, efetivamente implantado, combinou navegação e consulta para recuperar informações através de seleções espaciais e alfanuméricas. Através de exemplos foi mostrado que este tipo de solução auxilia gestores nos processos de exploração, análise e tomada de decisão. / Domestic waste illegally disposed constitute a serious problem, especially in large cities, causing clogging of drains and drainage with subsequent flooding, dirt and transmission of diseases such as leptospirosis and dengue as well as being a hindrance to traffic and would entail city hall costs. Moreover, recycle this material is a source of revenue and a generator of jobs. The Analytical Geovisualization can be of great help in the analysis of this complex problem and the decision-making. With this motivation, this paper seeks to provide an overview of the state of the art as the concepts and research in Geovisualization (GVis) and Analytical Processing (OLAP and SOLAP). It also presents processes, methodologies and technologies that were used in developing a prototype of an analytical system applied to the area of selective collection information management of recyclable solid waste in urban environments. This prototype, effectively deployed, combined navigation and query to retrieve information through spatial and alphanumeric selections. Through examples it was shown that this type of solution helps managers in operating procedures, analysis and decision making.