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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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Integration of Big Data and data warehouse
Kiška, Vladislav ; Novotný, Ota (advisor) ; Kerol, Valeria (referee)
Master thesis deals with a problem of data integration between Big Data platform and enterprise data warehouse. Main goal of this thesis is to create a complex transfer system to move data from a data warehouse to this platform using a suitable tool for this task. This system should also store and manage all metadata information about previous transfers. Theoretical part focuses on describing concepts of Big Data, brief introduction into their history and presents factors which led to need for this new approach. Next chapters describe main principles and attributes of these technologies and discuss benefits of their implementation within an enterprise. Thesis also describes technologies known as Business Intelligence, their typical use cases and their relation to Big Data. Minor chapter presents main components of Hadoop system and most popular related applications. Practical part of this work consists of implementation of a system to execute and manage transfers from traditional relation database, in this case representing a data warehouse, to cluster of a few computers running a Hadoop system. This part also includes a summary of most used applications to move data into Hadoop and a design of database metadata schema, which is used to manage these transfers and to store transfer metadata.
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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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Data Integration between Database Systems
Papež, Zdeněk ; Ščuglík, František (referee) ; Ráb, Jaroslav (advisor)
This master´s thesis deals with data integration that is used for data transfer within various database systems in both directions - data migration and replication. We become familiar with the technologies of distributed databases. In detail the system of health care providers is described and particular tables involved into its data integration are explored. For the project execution the proposal for integration of this system is created and whereupon following implementation is described.
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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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Impact of the process and data integration on reporting efficiency
Sys, Bohuslav ; Šebesta, Michal (advisor) ; Bruckner, Tomáš (referee)
Nowadays, when the difference between failure and success is amount of the available information combined with exponential growth of the available information on web leads to rising need to track the quality of the data. This worldwide trend is not only global, but it affects even individuals and companies in particular. In comparison with the past these companies produce higher amount of data, which are more complex at the same time, all to get a better idea about the real world. This leads us to the main problem, when we not only need to gather the data, but we have to present them in such way, so they can serve the purpose for which they have been gathered. Therefore the purpose of this thesis is to focus on processes following the data gathering -- data quality and transformation processes. In the first part of the thesis we will define a basic concept and issues, followed by methods necessary for acquiring requested data in expected quality, which includes the required infrastructure. In the second part of the thesis we will define real-life example and use the knowledge from previous part to design usable solution and deploy it into use. In conclusion we will evaluate the design compared to the result acquired from its real-life utilization.
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Evangelist Marketing of the CloverETL Software
Štýs, Miroslav ; Střížová, Vlasta (advisor) ; Tichý, Jan (referee)
The Evangelist Marketing of the CloverETL Software diploma thesis aims at proposing a new marketing strategy for an ETL tool - CloverETL. Theoretical part comprises chapters two and three. In chapter two, the thesis attempts to cover the ETL term, which - as a separate component of the Business Intelligence architecture - is not given much space in literature. Chapter three introduces evangelist marketing, explains its origins and best practices. Practical part involves introducing the Javlin, a.s. company and its CloverETL software product. After assessing the current marketing strategy, proposal of a new strategy follows. The new strategy is built on evangelist marketing pillars. Finally, benefits of the new approach are discussed looking at stats and data - mostly Google Analytics outputs.
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Master Data Integration hub - solution for company-wide consolidation of referrential data
Bartoš, Jan ; Slánský, David (advisor) ; Pour, Jan (referee)
In current information systems the requirement to integrate disparate applications into cohesive package is greatly accented. While well-established technologies facilitating functional and comunicational integration (ESB, message brokes, web services) already exist, tools and methodologies for continuous integration of disparate data sources on enterprise-wide level are still in development. Master Data Management (MDM) is a major approach in the area of data integration and referrential data management in particular. It encompasses the referrential data integration, data quality management and referrential data consolidation, metadata management, master data ownership, principle of accountability for master data and processes related to referrential data management. Thesis is focused on technological aspects of MDM implementation realized via introduction of centrallized repository for master data -- Master Data Integration Hub (MDI Hub). MDI Hub is an application which enables the integration and consolidation of referrential data stored in disparate systems and applications based on predefined workflows. It also handles the master data propagation back to source systems and provides services like dictionaries management and data quality monitoring. Thesis objective is to cover design and implementation aspects of MDI Hub, which forms the application part of MDM. In introduction the motivation for referrential data consolidation is discussed and list of techniques used in MDI Hub solution development is presented. The main part of thesis proposes the design of MDI Hub referrential architecture and suggests the activities performed in process of MDI Hub implementation. Thesis is based on information gained from specialized publications, on knowledge gathererd by delivering projects with companies Adastra and Ataccama and on co-workers know-how and experience. Most important contribution of thesis is comprehensive view on MDI Hub design and MDI Hub referrential architecture proposal. MDI Hub referrential architecture can serve as basis for particular MDI Hub implementation.
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State of the market for Enterprise Information Integration
Dohnal, Tomáš ; Gála, Libor (advisor) ; Pour, Jan (referee)
Diploma thesis deals with the topic of information integration. The aim of the thesis is to characterize the market of IT resources for supporting Enterprise Information Integration. To achieve its objective, it will be first introduced the area of EII. The results will serve for formulating criteria that will be used to analyze the market of these IT resources. Based on the formulated criteria, there will be evaluated market offerings and then specified its key characteristics. The author's contribution to this work lies in the submission of a comprehensive description of the Enetrprise Information Integration.
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