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Hadoop NoSQL database
Švagr, Lukáš ; Palovská, Helena (advisor) ; Tomášková, Barbora (referee)
The theme of this work is database storage Hadoop Hbase. The main goal is to demonstrate the principles of its function and show the main usage. The entire text assumes that the reader is already familiar with the basic principles of NoSQL databases. The theoretical part briefly describes the basic concepts of databases then mostly covers Hadoop and its properties. This work also includes the practical part which describes how to install a database repository and illustrates basic database operations in two simple programs. The components of the practical part are case studies that report current use of Hadoop in the world-famous companies.
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Application of Big Data in the banking environment
Dvorský, Bohuslav ; Chlapek, Dušan (advisor) ; Palovská, Helena (referee)
This thesis addresses the principles and technologies of Big Data and their usage in the banking environment. Its objective is to find business application scenarios for Big Data for purposes of delivering added value for the bank. Finding the scenarios have been achieved by studying literature and consultation with experts, they were also subsequently modeled by the author. Possibilities of application of these scenarios in the banking busi-ness environment were subsequently verified by the survey, which interviewed profession-als on issues relating to the found business scenarios. The thesis first explains the basic con-cepts and approaches of Big Data, the status of this technology compared to traditional technologies and issues of integration into the banking environment. After this theoretical beginning the business scenarios are found and modeled followed by the exploration and evaluation. Selected business scenarios are further verified for the purpose of determining the suitability or unsuitability for implementation using technologies and principles of Big Data. The contribution of this work is to find a real use of Big Data in banking, where most of the materials on this topic is very general and vague. This thesis verifies two business scenarios that can big a bank institution high added value if they are implemented with Big Data platform.
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Big Data analysis in healthcare
Nováková, Martina ; Kučera, Jan (advisor) ; Chlapek, Dušan (referee)
This thesis deals with the analysis of Big Data in healthcare. The aim is to define the term Big Data, to acquaint the reader with data growth in the world and in the health sector. Another objective is to explain the concept of a data expert and to define team members of the data experts team. In following chapters phases of the Big Data analysis according to methodology of EMC2 company are defined and basic technologies for analysing Big Data are described. As beneficial and interesting I consider the part dealing with definition of tasks in which Big Data technologies are already used in healthcare. In the practical part I perform the Big Data analysis task focusing on meteorotropic diseases in which I use real medical and meteorological data. The reader is not only acquainted with the one of recommended methods of analysis and with used statistical models, but also with terms from the field of biometeorology and healthcare. An integral part of the analysis is also information about its limitations, the consultation on results, and conclusions of experts in meteorology and healthcare.
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Data warehouse in the Amazon Web Services
Kuželka, Kryštof ; Palovská, Helena (advisor) ; Pour, Jan (referee)
The primary objective of this work is to investigate the potential of utilizing Hadoop and Amazon Redshift in the Amazon Web Services ("AWS") cloud, in order to design and implement a data warehouse, the efficacy of which will be tested afterwards. Contributions of this work include: documenting the technologies in the AWS cloud in Czech, demonstration of the design and performance tests of the data warehouse and the ETL part. Another considerable benefit is the added value to the company for whom the project was designed, and which is currently using the output of the project.
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New Trends in Business Intelligence - Focus on Big Data and Hadoop
Korkisch, Josef ; Vacek, Martin (advisor) ; Pour, Jan (referee)
The thesis is focused on several specific areas. The first area is the identification of new trends in the field of Business Intelligence in recent years. Furthermore, the thesis focuses on Big Data (Hadoop). The main purpose is to show the possible use of the Hadoop technology on real-world examples. What is also important, is a section dedicated to comparison of Business Intelligence tools for working with Big Data as it is the section which proofs standpoint from several significant aspects -- angels (analysis, visualization and connectivity). The work is divided into several parts in which the components of Business Intelligence, new trends in BI, Hadoop technology in the context of BI, Hadoop components are described, as well as examples of using Hadoop and comparison of selected BI tools to work with BI is introduced within the thesis. The main purpose of the thesis is to serve as a guide to the world of BI and Big Data (Hadoop).
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Big Data Analytics tools
Miloš, Marek ; Pour, Jan (advisor) ; Andrle, David (referee)
The thesis covers the term for specific data analysis called Big Data. The thesis firstly defines the term Big Data and the need for its creation because of the rising need for deeper data processing and analysis tools and methods. The thesis also covers some of the technical aspects of Big Data tools, focusing on Apache Hadoop in detail. The later chapters contain Big Data market analysis and describe the biggest Big Data competitors and tools. The practical part of the thesis presents a way of using Apache Hadoop to perform data analysis with data from Twitter and the results are then visualized in Tableau.
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Hadoop: HDFS, MapReduce and cmputing in IBM BigInsights
Fessl, Adam ; Řezáč, Miroslav (advisor) ; Novotný, Ota (referee)
This undergraduate thesis thematically appertains to the field of Big Data. Particularly, it concerns Hadoop, an open-source tool, serving for distributed processing and saving data. The object of this thesis is to provide the reader with theoretical knowledge and basic prin-ciples concerning the Apache Hadoop with concentration on the file system HDFS and model for distributed MapReduce computing. Theoretical knowledge and principles are illustrated on modified application WordCount in IBM InfoSphereBigInsights. This work consists of three parts. First part is dealing with Hadoop and its basic modules. Second one provides information concerning the prominent Hadoop distributors; special attention is given to IBM. The last part presents practical computing. This thesis offers a comprehensive view on Hadoop, which combines technical point of view with practical application. Both of them are illustrated on particular examples and supplemented with methods to operate Hadoop.
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Big Data, their storage and options of exploitation
Macek, Jáchym ; Chlapek, Dušan (advisor) ; Kučera, Jan (referee)
The content of this bachelor's thesis is to analyze work with data especially with large-volume unstructured data, thus Big Data. The thesis is retrieval and contents informational survey based on questionnaires and interviews. The aim is to evaluate and approximate Big Data theme, their storage, tools for their management and opportunities of its exploitation to the reader from technological and business point of view. The objective for the practical part is a survey. The thesis is divided in to three parts. The first part defines the concept, gives closer look at the issue and is dedicated to open and linked data. The second part deals with the question of storage and opportunities of subsequent exploitation of stored data, tools and technologies for Big Data management. Further, there is evaluation of the advantages and disadvantages and comparison of the Hadoop technologies. In the third part the survey of Big Data issue is published. I use tools of questionnaires and interviews for acquiring information from students and experts. Furthermore, it describes current trends, problems and offers solution from the field.
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Big Data and its perspective for the banking
Firsov, Vitaly ; Maryška, Miloš (advisor) ; Molnár, Zdeněk (referee)
In this thesis, I want to explore present (y. 2012/2013) modern trends in Business Intelligence and focus specifically on the rapidly evolving and, in my (and not only) opinion, a very perspective area of analysis and use of Big Data in large enterprises. The first, introductory part contains general information and the formal conditions as aims of the work, on whom the work is oriented and where it could be used. Then there are described inputs and outputs, structure, methods to achieve the objectives, potential benefits and limitations in this part. Because at the same time I work as a data analyst in the largest bank Czech Republic, Czech Savings Bank, I focused on the using of Big Data in the banking, because I think, that it is possible to achieve great benefits from collecting and analyzing Big Data in this area. The thesis itself is divided into 3 parts (chapters 2, 3-4, 5). In the second chapter you will learn, how developed the area of BI, how it evolved historically, what is BI today and what future is predicted to the BI by the experts like the world famous and respected analyst firm Gartner. In the third chapter I will focus on Big Data itself, what this term means, how Big Data differs from traditional business information available from ERP, ECM, DMS and other enterprise systems. You will learn about ways to store and process this type of data, as well as about the existing and applicable technologies, focused on Big Data analysis. In the fourth chapter I focus on the using of Big Data in business, information in this chapter will reflect my personal views on the potential of Big Data, based on my experience during practice in Czech Savings Bank. The final part will summarize this thesis, assess, how I fulfilled the objectives defined at the beginning, and express my opinion on perspective of the trend of Big Data analytics, based to the analyzed during the writing this thesis information and knowledge.
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Comparison of distributed "NoSQL" databases with focus on performance and scalability
Vrbík, Tomáš ; Šlajchrt, Zbyněk (advisor) ; Pavlíček, Luboš (referee)
This paper focuses on NoSQL database systems. These systems currently serve rather as supplement than replacement of relational database systems. The aim of this paper is to compare 4 selected NoSQL database systems (MongoDB, Apache Cassandra, Apache HBase and Redis) with a main focus on performance and scalability. Performance comparison is done using simulated workload in a 4 nodes cluster environment. One relational SQL database is also benchmarked to provide comparison between classic and modern way of maintaining structured data. As the result of comparison I found out that none of these database systems can be labeled as "the best" as each of the compared systems is suitable for different production deployment.
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