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Datová integrace ve velkých podnicích
Nagyová, Barbora ; Kučera, Jan (advisor) ; Chlapek, Dušan (referee)
Data Integration is currently an important and complex topic for many companies, because having a good and working Data Integration solution can bring multiple advantages over competitors. Data Integration is usually being executed in a form of a project, which might easily turn into failure. In order to decrease risks and negative impact of a failed Data Integration project, there needs to be good project management, Data Integration knowledge and the right technology in place. This thesis provides a framework for setting up a good Data Integration solution. The framework is developed based on the current theory, currently available Data Integration tools and opinions provided by experts working in the field for a minimum of 7+ years and have proven their skills with a successful Data Integration project. This thesis does not guarantee the development of the right Data Integration solution, but it does provide guidance how to deal with a Data Integration project in a large enterprise. This thesis is structured into seven chapters. The first chapter brings an overview about this thesis such as scope, goals, assumptions and expected value. The second chapter describes Data Management and basic Data Integration theory in order to distinguish these two topics and to explain the relationship between them. The third chapter is focused purely on Data Integration theory which should be known by everyone who participates in a Data Integration project. The fourth chapter analyses features of the current Data Integration solutions available on the market and provides an overview of the most common and necessary functionalities. Chapter five focuses on the practical part of this thesis, where the Data Integration framework is designed based on findings from previous chapters and interviews with experts in this field. Chapter six then applies the framework to a real working (anonymized) Data Integration solution, highlights the gap between the framework and the solution and provides guidance how to deal with the gaps. Chapter seven provides a resume, personal opinion and outlook.
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Open Government Data
Kučera, Jan ; Jandoš, Jaroslav (advisor) ; Richta, Karel (referee) ; Šaloun, Petr (referee)
This Ph.D. thesis deals with Open Government Data and the methodology for publication of this kind of data. Public sector bodies hold a significant amount of data that can be reused in innovative way leading to development of new products and services. According to the Open Knowledge Foundation "Open data is data that can be freely used, re-used and redistributed by anyone - subject only, at most, to the requirement to attribute and sharealike." Publication and reuse of Open Government Data can lead to benefits such as increased economic growth. State, society as well as the public sector bodies themselves can benefit from Open Government Data. However the public sector bodies currently face a number of problems and issues when publishing Open Government Data, e.g. regular updates of the published datasets are not always ensured. Different public sector bodies apply different approaches to publication of Open Government Data. The main goal of this thesis is to design the Open Government Data Publication Methodology which should address current problems related to the publication of Open Government Data.
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