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Stahování smluv z registru smluv
Kříha, Jakub ; Bruckner, Tomáš (advisor) ; Šperková, Lucie (referee)
The topic of this bachelor's thesis is development of a script for downloading and filtering entries from public registry of contracts of Ministry of the interior of the Czech Republic. This thesis is part of a project to create price-list of ICT work for state institutions. The goals of this thesis include introduction of the price-list project, draft of download script's functionality, description of follow-up data processing, trying out two different programming languages of the script and final deployment of chosen script in production. My thesis contributes to creation of price-list of ICT work, which is important for evaluating offers in open tenders.
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Data Mining for Effective Customer Communication
Madhi, Simona ; Šperková, Lucie (advisor) ; Novotný, Ota (referee)
The aim of this paper is to describe and illustrate benefits of using Data Mining for effective customer communication. The objective is to perform a Data Mining analysis in order to achieve results with potentially beneficial influence on the company s relationship with its customers, while using the KNIME Analytics Platform tool. The paper introduces the theoretical aspect of Customer Relationship Management, Data Mining and the opportunities of using Data Mining to improve CRM; followed by a market analysis of available Data Mining tools and the introduction of the KNIME Analysis Platform. Furthermore, the knowledge thus reached is used for the performance of real data analysis with the aim of reaching customer knowledge that would be appropriate to use within CRM strategy and finally to positively influence the value of customer relationships.
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Usage of unstructured data in Business Intelligence
Rakhmanova, Malika ; Šperková, Lucie (advisor) ; Karkošková, Soňa (referee)
The aim of the thesis is to identify the main trends that are occurring in the market of Business Intelligence and related to unstructured data, to describe the possibilities for integrating unstructured data, to clarify what the impact on the company have the results that can be obtained using these solutions and how generally incorporate an analysis of unstructured data into BI. Another aim is to show the current situation of processing unstructured data on the example of BI system. The thesis is divided into several parts. First part is describing of the Business Intelligence area and the basic components of Business Intelligence, as well as identifying market trends. Then, there is the next part: separating the data into structured and unstructured. Here is the part about how you can access and analyse unstructured data and what is their place in BI systems. This is the end of a block of unstructured data and the beginning of a description of the enhanced version of BI. Finally, the current market situation and BI tools, which include unstructured data, are introduced. This section provides an overview of how BI tools approach to analyse unstructured data. Existed literature, professional and freely available Internet resources are used for writing the work. The purpose is to serve as a source of information for quickly orienting in the current situation, to serve as a guide to the world of BI solutions and to show potential users what are the options and functionality of these BI solutions.
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Possibilities of Big Data use for Competitive Intelligence
Verníček, Marek ; Molnár, Zdeněk (advisor) ; Šperková, Lucie (referee)
The main purpose of this thesis is to investigate the use of Big Data for the methods and procedures of Competitive Intelligence. Among the goals of the work is a toolkit for small and large businesses which is supposed to support their work with the whole process of Big Data work. Another goal is to design an effective solution of processing Big Data to gain a competitive advantage in business. The theoretical part of the work processes available scientific literature in the Czech Republic and abroad as well as describes the current state of Competitive Intelligence, and Big Data as one of its possible sources. Subsequently, the work deals with the characteristics of Big Data, the differences from working with common data, the need for a thorough preparation and Big Data applicability for the methods of Competitive Intelligence. The practical part is focused on analysis of Big Data tools available in the market with regard to the whole process from data collection to the analysis report preparation and integration of the entire solution into an automated state. The outcome of this part is the Big Data software toolkit for small and large businesses based on their budget. The final part of the work is devoted to the classification of the most promising business areas, which can benefit from the use of Big Data the most in order to gain competitive advantages and proposes the most effective solution of working with Big Data. Among other benefits of this work are expansion of the range of resources for Competitive Intelligence and in-depth analysis of possibilities of Big Data usage, designed to help professionals make use of this hitherto untapped potential to improve market position, gain new customers and strengthen the existing user base.
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Corporate Performace Management in the Retail Area
Čencová, Klára ; Novotný, Ota (advisor) ; Šperková, Lucie (referee)
This Diploma thesis focuses on the alignment of regulatory processes to support corporate performance management in the selected retail company. The main objective is the preparation of process maps that serve as a basis for the implementation of a global standard for automatic exchange of financial account information, developed by the OECD, also called as Common Reporting Standard. Additionally, the partial objectives include analysis of existing forms of content-related processes, creating a methodological support to the created processes and the theoretical concepts of regulatory requirements. The theoretical part focuses on the introduction of concepts related to the corporate management performance and also on theory about specific regulatory regulation used. In the practical part is an analysis of the company through the Balanced Scorecard (BSC), followed by the actual design and process description. The main contribution of the Diploma thesis was to perform process optimization, along with some improvements during the creation of these processes. The company will use the outcomes in practice.
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Cross-channel attribution modelling
Žárský, Jiří ; Šperková, Lucie (advisor) ; Vraná, Lenka (referee)
This bachelor thesis focuses on attribution in the context of online marketing and studies available evaluation models for the performance of advertising campaigns. This performance is measured on the basis of the campaigns' effectiveness in catching the attention of customers and generating revenue. Data containing information about users' interactions with real advertising campaigns were used for the analysis. Prior to solving the attribution problem, data from the AdForm platform were cleansed and transformed into the required structures. This process is automated by the ETL tool called Keboola. Afterwards, data are analyzed using various attribution modelling techniques such as simple heuristics, the Shapley Value or Markov chains. The thesis discusses the theoretical side, as well as the actual application of these models. In the last section, the results of individual models are interpreted, taking into account the campaign costs. The interpretation is performed in the Tableau visualization software, using metrics such as the return on advertisement spending. This thesis presents a critical assessment of attribution models based on predetermined criteria. A scheme of data transformations, which can be used for future analyses of advertisement campaigns, was also created as part of this work. The thesis further includes a chapter discussing issues potentially leading to inaccuracies in the models' results.
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Hadoop and Business Intelligence
Kerner, Josef ; Šperková, Lucie (advisor) ; Augustín, Jakub (referee)
The main purpose of this thesis is to describe how an integration of a Hadoop platform into currently existing Business Intelligence technologies and processes can augment its data processing and analysis capabilities while encountering Big Data. Furthermore, it describes reasons why the whole Hadoop application ecosystem was founded and informs the reader about the functionality of its primary components. It continues with provision of overview about Hadoop higher-level components architecture and their use in existing Business Intelligence processes such as data ingestion, transformation and analysis. In the last theoretical chapter it focuses itself on describing specific areas of utilization of the Hadoop platform and Big Data in data warehousing, text mining and predictive analytics. From the practical point of view, a particular use case is provided, an implementation of Big Data ETL process in the field of financial markets and trading with a detailed explanation of the corresponding necessities such as data model, ETL code and proposed metrics, which can be further implemented for achieving increased return on investments.
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Security in hybrid cloud computing
Koudelka, Ondřej ; Karkošková, Soňa (advisor) ; Šperková, Lucie (referee)
This bachelor thesis deals with the area of hybrid cloud computing, specifically with its security. The major aim of the thesis is to analyze and compare the chosen hybrid cloud providers. For the minor aim this thesis compares the security challenges of hybrid cloud as opponent to other deployment models. In order to accomplish said aims, this thesis defines the terms cloud computing and hybrid cloud computing in its theoretical part. Furthermore the security challenges for cloud computing are defined and specified for hybrid cloud. The comparison of specific hybrid cloud providers is provided in the practical part along with the comparison of hybrid cloud security challenges.
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Modernization of public ground transport through the use of 21st century technologies
Lokajíček, Miloš ; Bruckner, Tomáš (advisor) ; Šperková, Lucie (referee)
The thesis deals with the benefits of modern technologies to public land transport, an area which has not been notably impacted by modern technologies to this day. The work anal-yses both the way modern technologies can help transport companies, and also which tech-nologies in particular can bring something new to the conservative sector. The specific ob-jectives of the thesis are the analysis of D2D systems key components, benefits of Yield Management to the transport industry and implementation of carriers into the Bileto plat-form.
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