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Internet of Things Device Based on ZigBee and 6LoWPAN
Halász, Dávid ; Mlích, Jozef (referee) ; Musil, Petr (advisor)
Internet of Things is the latest phenomenon in the computing industry. Even if it has not been completely defined yet, we are already surrounded by various devices connected to the Internet. This thesis project focuses on low cost and low-power wireless solutions and on the on-line backend behind the architecture. At the same time the present work also deals with Cloud Computing which can provide a highly scalable runtime environment for this backend without building an infrastructure. To handle the huge amount of data collected by billions of devices, BigData services could be used in the same cloud space. The project is a collection of the theoretical background of the Internet of Things; so as a result, it provides the reader with an overview of the concept. It also provides a walktrough of the design, implementation and testing process of a complex agricultural Internet of Things solution.
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Analysis of Czech football from the content of social networks
Zálepa, Martin ; Jelínek, Ivan (advisor) ; Oškera, Radek (referee)
The main aim of this report is to analyse the Czech football scene using the unstructured data from ever evolving social media platform Facebook. The objectives are to identify key concepts using the Czech football social community, dis-covering the most popular club, understanding the buzz and reactions on independent sport portals and identifying the relation between social sentiment and the actual football club performance. These objectives are met using defined methods including collection, analysis and evaluation of the data, applying the key data metrics and relevant literature research, as well as graphical visualisation of the results. This report consists of five chapters split into theoretical and practical part. The first three chapters, the theoretical part, are focusing on the explanation of the social media in general, using the literature research and online analytical tools, and introduction of the Czech foot-ball scene from both commercial and marketing standpoint. The last chapter describes the methods applied and outlines the data architecture used for the analysis. The practical part includes a definition of the key metrics that are initially defined as business assumptions and consequently applied and transformed into the basis of this analysis. The last chapter of the practical part forms the actual data analysis and its evaluation as well as visualisation of the partial results. The main purpose of this report is to demonstrate the benefits of analysing unstructured data from social media platforms that can be connected and downloaded using the tools such as Elasticsearch and Kibana, that enable to discover, filter and visualise the data. Gaining an insight into social media and visualisation of the data is also beneficial to spon-sors and football clubs as it can maximise the power of their marketing as well as enable them to understand the reputation and consumer perception.
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Machine learning in the field of Big Data
Šimánek, Michal ; Kerol, Valeria (advisor) ; Novotný, Ota (referee)
This bachelor's thesis devotes to the field of machine learning in Big Data. The main aim is to map and evaluate current situation of machine learning in Big Data, select and compare the most used machine learning libraries in Apache Spark tool and provide guide, how to implement algorithms of selected libraries. Theoretical part consists of explaining concept of Big Data, tools Apache Hadoop and Apache Spark, machine learning and decribes most used machine learning libraries in the Apache Spark tool along with comparsion metrics. Practical part is oriented to implementation of algorithms of selected libraries, writing the guide for implementation and according to outcomes and implementations comparing selected libraries from different views. Contribution of this thesis is to introduce machine learning problematics in Big Data, describe most used machine learning libraries and compare selected libraries with providing guide how to implement their algorithms.
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Automatizace nákupu
Cizner, Pavel ; Vinš, Marek (advisor) ; Jirsák, Petr (referee)
The research goal was to find out the current and possible level of procurement automation and its contribution to less routine and more creative jobs. The goal was accomplished by literature review and data collection via survey. The data collected evaluated enterprises in developing and developed countries. The research hypothesis of developing countries automating more than developed ones was not supported by the data tested via Mann-Whithey U test. The data collected was from 146 respondents from all around the world. Therefore, there are limitations of the conclusions. The thesis and its survey contributes to the knowledge about the level of procurement automation.
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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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Application of text mining methods for analysis of users movie reviews
Palatínus, Vojtěch ; Matějka, Martin (advisor) ; Novotný, Ota (referee)
The topic of this thesis is to define the challenges while working with the unstructured data. It focuses, specifically, on a transformation between unstructured and structured data using text mining methods and bringing the closer view on so-called Big Data phenomenon. The goal of this thesis is to introduce problems that occur when working with unstructured data, to show their transformation to structured data format using text mining methods and to perform analysis on user reviews published on the website of The Internet Movie Database from the mined data. The aim of this thesis is to familiarize the reader with the unstructured data and on the example demonstrate how to use text mining methods for mining relevant information from this type of data.
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Apache Hadoop as analytics platform
Brotánek, Jan ; Novotný, Ota (advisor) ; Kerol, Valeria (referee)
Diploma Thesis focuses on integrating Hadoop platform into current data warehouse architecture. In theoretical part, properties of Big Data are described together with their methods and processing models. Hadoop framework, its components and distributions are discussed. Moreover, compoments which enables end users, developers and analytics to access Hadoop cluster are described. Case study of batch data extraction from current data warehouse on Oracle platform with aid of Sqoop tool, their transformation in relational structures of Hive component and uploading them back to the original source is being discussed at practical part of thesis. Compression of data and efficiency of queries depending on various storage formats is also discussed. Quality and consistency of manipulated data is checked during all phases of the process. Fraction of practical part discusses ways of storing and capturing stream data. For this purposes tool Flume is used to capture stream data. Further this data are transformed in Pig tool. Purpose of implementing the process is to move part of data and its processing from current data warehouse to Hadoop cluster. Therefore process of integration of current data warehouse and Hortonworks Data Platform and its components, was designed
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Forms of abuse of Dominance in the Area of the Internet Platform
Čížek, Ondřej ; Šmejkal, Václav (advisor) ; Vondráčková, Aneta (referee)
Forms of abuse of dominance in the area of the Internet platforms The thesis is dedicated to the topic of abuse of dominant position in the area of the Internet platforms. Its aim is, firstly, to outline the challenges arising from the specific nature of the area, which might, from the competition-authorities' point of view, complicate the enforcement of competition law in the case of abuse of dominance. Secondly, the thesis tries to find the answer on the question to what extent these problems have been reflected in the existing decision-making practice. The structure of the thesis is divided into four main parts. The first part is an introduction. The second part provides an essential introduction to the area in question. It defines the term "Internet platform", provides an overview of the most important types of the Internet platforms and describes the specifics of the area in question, whose description is essential for the following parts. The third part analyses the problems that competition law may face in the context of possible abuse of dominance within the meaning of Art. 102 TFEU in the area of the Internet platforms. This section is divided according to three basic steps of a competition analysis of abuse of dominance, i.e. definition of the relevant market, the determination of market...
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Analytical methods for measurement error estimation in survey data
Chylíková, Johana ; Vinopal, Jiří (advisor) ; Kreidl, Martin (referee) ; Buriánek, Jiří (referee)
Analytical methods for measurement error estimation in survey data This dissertation aims at the domain of measurement error in social science survey data. To conceptualize and estimate measurement errors it employs the analytical and theoretical framework that stems from the analytical method of structural equation modeling (SEM) and Classical Test Theory (CTT), extended with the component of the systematic measurement error. This thesis has two goals that may contribute to development and extension of Czech social science methodology. The first goal is to illustrate methods of measurement error estimation, which has not been used for analysis of Czech data yet, and to point out to some problematical aspects of these methods. The second goal is to employ presented methods to obtain new findings regarding the quality of data from Czech surveys. The dissertation presents three empirical studies, each of which uses one of the methods defined within the presented theoretical and analytical framework. First study presents an analysis of reliability of measurement with the Quasi Simplex Model (QSM). It illustrates how to use the model and brings optimistic results regarding the reliability of the Czech EU SILC panel data. In the second study the confirmatory factor analysis model, operationally called...
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Transformation of journalistic practices relating to advent of data journalism
Ďuríčková, Monika ; Dvořák, Tomáš (advisor) ; Nečas, Vlastimil (referee)
The diploma thesis titled Transformation of Journalistic Practices Relating to Advent of Data Journalism concerns the current situation in Czech data journalism and its devel- opment. It examines how the newsroom, the journalists and the readers cope with new technology, big data and the related advent of data journalism. The theoretical part of the text explains the relationship between classical journalism and data-driven journal- ism and compares the so-called "narrative" and "interactive" approaches as forms of data-driven journalism. Further it gives a deeper understanding of the relation between data journalism and the new concept of objectivity and it deals with the cultural, social and technical preconditions of data journalism. The thesis also describes the historical aspects of the topic comparing computer-assisted reporting to current practice. Sub- sequent chapters deal with the visualizations, infographics, amateur data journalism and open data which all play a key role in data-driven journalism. The practical part intro- duces the Czech data team. It was originally established within the publishing house Economia and then moved to the office of Czech Radio (Český rozhlas). The final parts discuss the cooperation model of the Czech data team, the use of visualization in their projects,...
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