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Prediktívna analytika v retailovom bankovníctve v Českej republike
Búza, Ján ; Král, Petr (advisor) ; Tyl, Ondřej (referee)
Advanced analytics and big data allow a more complete picture of customers' preferences and demands. Through this deeper understanding, organizations of all types are finding new ways to engage with existing or potential customers. Research shows that companies using big data and advanced analytics in their operations have productivity and profitability rates that are 5 to 6 percent higher compared to their peers. At the same time it is almost impossible to find a banking institution in the Czech Republic exploiting potential of data analytics to its full extent. This thesis will therefore focus on exploring opportunities for banks applicable in the local context, taking into account technological and financial limitations as well as the market situation. Author will conduct interviews with bank managers and management consultants familiar with the topic in order to evaluate theoretical concepts and the best practices from around the world from the point of Czech market environment, to assess capability of local banks to exploit them and identify the main obstacles that stand in the way. Based on that a general framework for bank managers, who would like to use advanced analytics, will be proposed.
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Cloud computing and its introduction in small and medium sized enterprises
Šimonfy, Adam
Simonfy, A. Cloud computing and its introduction in small and medium enterpris-es. Bachelor thesis. Brno: Mendel University in Brno, 2015. This thesis is compiled on the Cloud computing and its introduction in the small and medium enterprises and evaluation of its connection to the up-coming tech-nologies and chosen factors connected to the operations management with the stress on costs. Cloud computing shows strong benefits for the business. The study of selected model company showed that it is justified for a company to con-sider the technology, however, it might not be applicable for all kinds of small and medium enterprises.
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Robust Regularized Cluster Analysis for High-Dimensional Data
Kalina, Jan ; Vlčková, Katarína
This paper presents new approaches to the hierarchical agglomerative cluster analysis for high-dimensional data. First, we propose a regularized version of the hierarchical cluster analysis for categorical data with a large number of categories. It exploits a regularized version of various test statistics of homogeneity in contingency tables as the measure of distance between two clusters. Further, our aim is cluster analysis of continuous data with a large number of variables. Various regularization techniques tailor-made for high-dimensional data have been proposed, which have however turned out to suffer from a high sensitivity to the presence of outlying measurements in the data. As a robust solution, we recommend to combine two newly proposed methods, namely a regularized version of robust principal component analysis and a regularized Mahalanobis distance, which is based on an asymptotically optimal regularization of the covariance matrix. We bring arguments in favor of the newly proposed methods.
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High-Performance Analytics (HPA)
Soukup, Petr ; Pour, Jan (advisor) ; Novotný, Ota (referee)
The aim of the thesis on the topic of High-Performance Analytics is to gain a structured overview of solutions of high performance methods for data analysis. The thesis introduction concerns with definitions of primary and secondary data analysis, and with the primary systems which are not appropriate for analytical data analysis. The usage of mobile devices, modern information technologies and other factors caused a rapid change of the character of data. The major part of this thesis is devoted particularly to the historical turn in the new approaches towards analytical data analysis, which was caused by Big Data, a very frequent term these days. Towards the end of the thesis there are discussed the system sources which greatly participate in the new approaches to the analytical data analysis as well as in the technological solutions of High Performance Analytics themselves. The second, practical part of the thesis is aimed at a comparison of the performance in conventional methods for data analysis and in one of the high performance methods of High Performance Analytics (more precisely, with In-Memory Analytics). Comparison of individual solutions is performed in identical environment of High Performance Analytics server. The methods are applied to a certain sample whose volume is increased after every round of executed measurement. The conclusion evaluates the tests results and discusses the possibility of usage of the individual High Performance Analytics methods.
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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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Eight ICT trends that will change libraries
Černý, Michal
Informační společnost i rychle se rozvíjející ICT proměňují vše kolem nás – od vzdělávání, přes dopravu až třeba právě po knihovny. Příspěvek představí osm technologií, které do deseti let začnou měnit knihovny téměř k nepoznání: Internet věcí; big data; veřejné multimediální displeje; firemní sociální sítě; cloud; nové mobilní sítě; zpracování přirozeného jazyka či sémantické technologie. Co bude tato změna znamenat pro knihovny? Jak se změní jejich postavení v informační společnosti?
Video:  MP4
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The influence of trends in BI project
Kapitán, Lukáš ; Pour, Jan (advisor) ; Rezek, Tomáš (referee)
The aim of this these is to analyse the trends occurring in Business intelligence. It does examine, summarise and judge each of the trends from the point of their usability in the real world, their influence and modification of each phase of the implementation of Bussiness intelligence. It is clear that each of these trends has its positives and negatives which can influence the statements in the evaluation. These factors are taken into consideration and analysed as well. The advantages and disadvantages of the trends are occurring especially in the areas of economical demand and technical difficultness. The main aim is to compare the methods of implementation of Bussiness intelligence with actual trends in BI. In order to achieve this a few crucial points were set: to investigate recent trends in the BI and to define the methods of implementation in the broadest terms. The awaited benefit of this these is already mentioned investigation and analysis of trends in the area of Bussiness intelligence and its use in implementation.
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Big data - application in banking
Uřídil, Martin ; Slánský, David (advisor) ; Pour, Jan (referee)
There is a growing volume of global data, which is offering new possibilities for those market participants, who know to take advantage of it. Data, information and knowledge are new highly regarded commodity especially in the banking industry. Traditional data analytics is intended for processing data with known structure and meaning. But how can we get knowledge from data with no such structure? The thesis focuses on Big Data analytics and its use in banking and financial industry. Definition of specific applications in this area and description of benefits for international and Czech banking institutions are the main goals of the thesis. The thesis is divided in four parts. The first part defines Big Data trend, the second part specifies activities and tools in banking. The purpose of the third part is to apply Big Data analytics on those activities and shows its possible benefits. The last part focuses on the particularities of Czech banking and shows what actual situation about Big Data in Czech banks is. The thesis gives complex description of possibilities of using Big Data analytics. I see my personal contribution in detailed characterization of the application in real banking activities.
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Google BigQuery and other Google tools for big data
Hráček, Filip
You have a lot of data. You kind of know what you want to do with them, but every operation would take minutes or hours to complete on your machine(s). Google BigQuery, Refine and FusionTables are some of the tools that help you harness the cloud - so you can do complex things with huge data in very short amounts of time.
Slides: idr-495_1 -  PDF
Video: idr-495_2 - MP4
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Challenges for CIO
Kouřimský, Vlastimil ; Benáčanová, Helena (advisor) ; Pour, Jan (referee)
The diploma thesis deals with the issue of the chosen current trends of ICT. The CIO represents the crucial person of the whole thesis. The aim of the thesis is to describe and comment on the connection of the role of the CIO with trends and challenges he/she has to face in recent times. To fulfill this aim it is necessary to realize the current trends through the integration of surveys of the renowned companies dealing with the ICT market. The field overhang of these studies dedicated to technologies is essential. The benefit of the thesis consists of the connection of the business and ICT at the CIO level. The abstraction from technical specifications of the particular trend as well as from the managerial point of view creates an image of the challenges for the CIO in the company context. The introductory part of the thesis reflects the position of ICT in companies and creates an image of the internal connection of the company as a whole. The core of the main part of the thesis contains chapters dedicated to the trends in particular: data analysis, content analysis, social business, big data, ICT security and education. Each of these main chapters describes the current state of the ICT field and its role in the company context. The last part of each main chapter deals with the benefit and the role of the CIO for the mentioned field. CIO's influence on the challenge, allies and possible risks of the trend are mentioned. At the end of the thesis the benefit of the CIO for the company and his/her role of facing challenges which come from the ICT field are evaluated. CIO plays an important role as a responsible person for particular challenges. Nevertheless, as it is apparent from the thesis, the CIO is not the only important part of the system that is necessary to create the maximum from each challenge.
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