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Computer-aided data quality monitoring and assessment in clinical research
Šiška, Branislav ; Kolářová, Jana (referee) ; Schwarz, Daniel (advisor)
The diploma thesis deals with the monitoring and evaluation of data in clinical research. Usual methods to identify incorrect data are one-dimensional statistical methods per each variable in the register. Proposed method enters directly into database and finds out outliers in data using machine learning combined with multidimensional statistical methods that transform all column variables of clinical register to one, representing one record of patient in the register. Algorithm of proposed method is written in Matlab.
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Implementace Business Intelligence v MVNO
Kamenchshikova, Alena ; Pour, Jan (advisor) ; Basl, Josef (referee)
The goal of this paper is to implement Business Intelligence solution for mobile virtual network operator Erbia Mobile. The first part is devoted to description and analysis of concepts and architecture associated with BI implementation. The second part deals with technical aspects of BI introduction to the company based on listed requirements gathered from series of interviews with management. Implementation is initiated by analysis of company data sources and detailed description of attributes essential to the telecommunication industry. Based on requirements and data source examination outputs, multidimensional analysis is created and described in detail. Next part describes individual components (Data Warehouse, ETL, OLAP cubes) implementation as well as different optimization techniques. Given components created on Microsoft platform using Integration, Analysis and Reporting Services. Final reports and dashboard visualizations are created using MS Excel and Power BI software tools.
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Data quality and its analysis in a non-bank loan company
Vránek, Pavel ; Maryška, Miloš (advisor) ; Espinoza, Felix (referee)
This bachelor thesis is focused on complex elaboration of the subject data quality from the theoretical description of working with data in an information system, through the data quality definition, description of the causes of poor quality of data and consequences, which poor data quality brings, to analyze the quality of data in the non-bank load company. For the analysis of the data quality will be first selected suitable dimensions of data quality, for which will be subsequently defined metrics. These metrics will be then measured over a real data using SQL query language and software designed for the analysis of data quality. The main contribution of this work is complex processing of data quality issues and a demonstration of the real state of data quality in the non-bank loan company. The work offers the possibility of extending the draft procedures and rules for data quality management.
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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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Linked Data Integration
Michelfeit, Jan ; Knap, Tomáš (advisor) ; Klímek, Jakub (referee)
Linked Data have emerged as a successful publication format which could mean to structured data what Web meant to documents. The strength of Linked Data is in its fitness for integration of data from multiple sources. Linked Data integration opens door to new opportunities but also poses new challenges. New algorithms and tools need to be developed to cover all steps of data integration. This thesis examines the established data integration proceses and how they can be applied to Linked Data, with focus on data fusion and conflict resolution. Novel algorithms for Linked Data fusion are proposed and the task of supporting trust with provenance information and quality assessment of fused data is addressed. The proposed algorithms are implemented as part of a Linked Data integration framework ODCleanStore.
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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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Data quality in the business information database environment
Cabalka, Martin ; Chlapek, Dušan (advisor) ; Kučera, Jan (referee)
This master thesis is concerned with the choice of suitable data quality dimensions for a particular database of economy information and proposes and implements metrics for its assessment. The aim of this paper is to define the term data quality in the context of economy information database and possible ways to measure it. Based on dimensions suitable to observe, a list of metrics was created and subsequently implemented in SQL query language, alternatively in a procedural extension Transact SQL. These metrics were also tested with the use of real data and the results were provided with a commentary. The main asset of this work is its complex processing of the data quality topic, from theoretical term definition to particular implementation of individual metrics. Finally, this study offers a variety of both theoretical and practical directions fort this issue to be further researched.
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