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Effectivity assessment of the implementation of the reporting system
Řežábek, Martin ; Lorenc, Miroslav (advisor) ; Vladyka, Štěpán (referee)
Thesis is focused on effectivity assessment of the reporting system of the selected company and the comparison of the former and current reporting solution. This is achieved by the appropriate literature research, creation of the individual assessment model based on the methodology of the analogy from the information systems assessment and based on the experience of the selected company's employees and the experience of the experts in the field of corporate financial management with the focus on the reporting systems. Model is defined by the set of criteria structured into the groups and by the weights assigned to criteria along with the value for each of them. The last phase consists of stepping out of the individual assessment and defines the generally applicable model, usable on the wide range of different reporting systems.
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Data comparability in knowledge discovery in databases
Horáková, Linda ; Chudán, David (advisor) ; Svátek, Vojtěch (referee)
The master thesis is focused on analysis of data comparability and commensurability in datasets, which are used for obtaining knowledge using methods of data mining. Data comparability is one of aspects of data quality, which is crucial for correct and applicable results from data mining tasks. The aim of the theoretical part of the thesis is to briefly describe the field of knowledqe discovery and define specifics of mining of aggregated data. Moreover, the terms of comparability and commensurability is discussed. The main part is focused on process of knowledge discovery. These findings are applied in practical part of the thesis. The main goal of this part is to define general methodology, which can be used for discovery of potential problems of data comparability in analyzed data. This methodology is based on analysis of real dataset containing daily sales of products. In conclusion, the methodology is applied on data from the field of public budgets.
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Adolescent's attitudes in public opinion research, data quality and reliability
Šlégrová, Petra ; Vinopal, Jiří (advisor) ; Podaná, Zuzana (referee)
The diploma thesis focuses on the youngest age cathegory of respondents in public opinion polls. The main goal is to examine character and quality of information about adolescent's attitudes and opinions obtained in public opinion polls that are held by The Public Opinion Research Centre. To achieve the main goal nonattitude is examined. The thesis will be divided into theoretical and practical part. Theoretical part stands on the basis of public opinion sociology and developmental psychology and the issue of attitude measurement is introduced along with adolescents developmental theory and characteristics. Practical part reflects the information summoned in theoretical part and test them on data collected by The Public Opinion Research Centre which were obtained in continuous research within project Our society. Analysis focuses on examination of nonresponse, don't know answers and neutral attitudes. Results are compared among all age groups.
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Deduplication methods in databases
Vávra, Petr ; Kyjonka, Vladimír (advisor) ; Skopal, Tomáš (referee)
In the present work we study the record deduplication problem as an issue of data quality. We define duplicates as records having different syntax and the same semantics and which are representing the same real-world entity. The main goal of this work is to provide the overview of existing deduplication methods according to their requirements, results and usability. We focus on the comparison of two groups of record deduplication methods - with and without the domain knowledge. Therefore, the second part of this work is dedicated to the implementation of our method which does not utilize any domain knowledge and compare its results with the results of commercial tool deeply utilizing the domain knowledge.
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IBM Cognos Report Studio jako efektivní nástroj reportingu v oblasti lidského kapitálu
Zinchenko, Yulia ; Pour, Jan (advisor) ; Obolenskiy, Vladimir Obolenskiy (referee)
Main topic discussed in this diploma thesis is corporate reporting in terms of Human Capital using Business Intelligence tools, specifically IBM Cognos Report Studio. One of the objectives is to show step-by-step methodology of creating complex dynamic report, which includes data structure modeling, layout design and quality check. Another objective is to conduct Cost-Benefit Analysis for a real-life project, which is focused on recreating of Excel-based report in Cognos-based environment in order to automate information flows. Essential part of the diploma thesis is theoretical background of Business Intelligence aspects of data quality and visualization as well as purposes of human capital reporting and description of appropriate KPIs. Objectives are addressed by conducting analysis and research of resources related to topics described above as well as using IBM Cognos Report Studio provided by one of the major companies in financial advisory field. This diploma thesis represents relevant reading for those, who are interested in real-life application of data quality improvement and information flow automation using Business Intelligence reporting tools.
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Towards Complex Data and Information Quality Management
Pejčoch, David ; Rauch, Jan (advisor) ; Máša, Petr (referee) ; Novotný, Ota (referee) ; Kordík, Pavel (referee)
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
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Data quality management in small and medium enterprises
Zelený, Pavel ; Pour, Jan (advisor) ; Novotný, Ota (referee)
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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Maintaining data quality in corporate information system
Rufer, Filip ; Maryška, Miloš (advisor) ; Dvořák, Stanislav (referee)
Hlavním cílem této práce je představit na základě teoretických poznatků a vlastních znalostí problematiku zajišťování kvality dat v podnikových informačních systémech, neboť kvalita dat se vzhledem k jejich rostoucímu objemu stává stále více aktuální. Práce nejprve podává teoretický pohled na podniková data, na chyby v nich vznikající a poté zkoumá důsledky jejich nedostatečné kvality. Ve druhém oddíle popisuje způsoby uchování dat, které v dnešní době kvalitě dat napomáhají. Třetí oddíl je věnován problematice uživatelských rozhraní a je jím dotvořen teoretický základ po oddíl čtvrtý, který přináší vlastní pohled na stav této problematiky a vyvozuje na jeho základě některá opatření, která by mohla zlepšení kvality dat v podnikových informačních systémech značně napomoci.
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