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Exploratory Analysis of Big Data in "jmenomesto"
Trampeška, Václav ; Plchot, Oldřich (referee) ; Landini, Federico Nicolás (advisor)
Tato práce se zabývá analýzou databáze online hry Jméno, město. V této hře mají hráči za úkol adekvátně odpovídat na zadané kategorie odpovědmi začínající na zadané písmeno. Práce analyzuje evoluci chování hráčů během existence hry a chování hráčů v různých zemích a kulturách v rámci stejného i jiného jazyka na základě popularity různých odpovědí. Pro zjednodušení vykonávání těchto analýz byla vyvinuta webová aplikace umožňující snadnou kolekci a vizualizaci dat v grafech bez nutnosti znalosti databázové struktury a dotazovacího jazyka. Výsledky navržených analyzačních metod jsou porovnávány s daty služby Google Trends za účelem zjištění podobností mezi daty sledovanými ve hře a internetovým vyhledáváním. Z toho porovnání vyplývá, že navržené metody mohou dávat smysluplné výsledky a databáze tedy může být vhodnou pro vykonávání dalších konkrétně zaměřených analýz. Práce dále, i na základě výsledků analýz, navrhuje změny pro zlepšení hry v rámci hráčského prožitku a výdělečnosti.
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Smart metering data analytics
Ševčík, Prokop ; Klusáček, Jan (referee) ; Drápela, Jiří (advisor)
The thesis focuses on using data from smart meters based on two-way communication in distribution system. It describes hardware structure of smart meter and measurements of electrical quantities. The thesis summarizes multiple smart metering use cases in DS. It reviews actual implementation of use cases in DS and it evaluates data available from smart meters. Data analytics tools for DS analysis are presented based on possible use cases
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Application for monitoring and analysis of vascular reconstructions
Drozen, Jan ; Hoksza, David (advisor)
Implantation and the care of vascular reconstructions and accesses for haemodialysis is one of areas of cardiovascular surgery. Both vascular reconstructions, known as bypasses, and prosthetic haemodialytic accesses, known as grafts, are used only if conventional therapies are unsuccessful. Thus effectivity of these operations is critically important for patient survival. The aim of this thesis is development of software system for evidence data obtained during vascular operations and following checkups. Important is also support for basic analytical and statistical processing of collected data. Another goal is to transform collected data into knowledge useful for increasing effectivity of vascular operations.
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Analysis of Firm’s Digital Marketing Communication Channels and Improvement Proposals
Peša, Jakub ; MBA, Jaroslav Palla, (referee) ; Chlebovský, Vít (advisor)
Diplomová práce se zabývá marketingovými komunikačními kanály vybrané společnosti, s digitálním zaměřením. Práce je zkomponována na principu datové analýzy a návrhu zlepšení pro firmu, se záměrem implementace. Rozsah práce zahrnuje teoretická východiska, výzkum prostředí společnosti a anlýzu e-marketingových dat, sbíraných firmou. Na základě těchto částí je založen návrh vylepšení, včetně odhadu nákladů a návrhu monitorování. Výstup práce je ve formě zlepšení efektivity marketingové komunikace firmy.
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Data Mining Case Study in Python
Stoika, Anastasiia ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis focuses on basic concepts and techniques of the process known as knowledge discovery from data. The goal is to demonstrate available resources in Python, which enable to perform the steps of this process. The thesis addresses several methods and techniques focused on detection of unusual observations, based on clustering and classification. It discusses data mining task for data with the limited amount of inspection resources. This inspection activity should be used to detect unusual transactions of sales of some company that may indicate fraud attempts by some of its salespeople.
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Data Mining with Python
Krestianková, Tamara ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with principles of data mining process, available Python packages for data mining and a demonstration of Python script capable of data analyisis focused on classification techniques. Created classifiers are able to classify subjects into two groups - healthy people and people suffering from Parkinson's disease - based on their biomedical vocal analysis data.
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Social Media Networks in Human Resources Management (Model Supporting a Recruitment of Employees)
Böhmová, Lucie ; Střížová, Vlasta (advisor) ; Basl, Josef (referee) ; Horváthová, Petra (referee)
The main goal and contribution of this thesis are to create an artifact in the form of model that supports a recruitment of employees via social media networks and its implementation into practice. For this purpose has been used a depth analysis of current state of researched problematics leading to finding gaps that could be eventually solved while using mentioned model. The Author takes advantage of knowledge obtained from literature research and also from self-created research, particularly the analysis of content type investigated social media networks and specific data obtained manually and automatically; Comparative analysis of job advertisements; periodic questionnaire survey amongst HR staff. A significant part of the research has also been an investigation of already existing frames of social media networks recruitment. A depth analysis of current state determines that there is existence only of few models dealing with social media networks recruiting. Furthermore, these models lack candidate evaluation based on the social media networks behavior. Artifact as a model that supports a recruitment of employees via social media networks contains a suggestion of an automatic solution dealing with user´s data downloading and also a suggestion of subsequent analytical data processing and the creation of a predictive model for assessing the user´s behavior on the social media networks. Final evaluation of the effectiveness of the proposed model is done through the formal verification process and the case study. The case study verification has the suggested artifact been implemented in practice with a name Model PM that is using a recruiting application (Práce na míru) for an extraction of Facebook´s data. For user´s behavior predictor setting has been used a character test (MBTI). With the help of the cluster analysis and machine learning (Decision trees) has been created Stochastic predictive model that determines a character type of particular candidate (The accuracy of the prediction of the MBTI personality category is in the range between 68 % to 84 % in individual cases with confidence value between 43 % and 81 %). The case study verified a usefulness of model that supports a recruitment of employees via social media networks, and afterward, the mode has been implemented into the practice.
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Current trends in customer relationship management
Kotara, Jan ; Jesenský, Daniel (advisor) ; Koudelková, Petra (referee)
The bachelor thesis "Current trends in customer relationship management" deals with - as its title suggests - the issue of CRM and selection of modern factors, which influence its current state. The theoretical part of the thesis presents the definition of customer relationship management and its position in the marketing theory, as well as a brief look into its history. It also contains a section about the specifics of CRM in retail sector, as it is further discussed in the practial part. The explanation of the importance of data and its analysis for CRM is followed by the most important section of the theoretical part about current trends in CRM - especially modern loyalty programs, omnichannel stratégy and social CRM. In the practical part of the thesis these findings are compared with the state of implementation of these trends in the retail chain Tesco. The aim of the thesis is to find the imperfections of the implementation of trends at Tesco and suggest ideas of improvement in order to enhance its customer relationship management.
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Application for monitoring and analysis of vascular reconstructions
Drozen, Jan ; Hoksza, David (advisor) ; Škoda, Petr (referee)
Implantation and the care of vascular reconstructions and accesses for haemodialysis is one of areas of cardiovascular surgery. Both vascular reconstructions, known as bypasses, and prosthetic haemodialytic accesses, known as grafts, are used only if conventional therapies are unsuccessful. Thus effectivity of these operations is critically important for patient survival. The aim of this thesis is development of software system for evidence data obtained during vascular operations and following checkups. Important is also support for basic analytical and statistical processing of collected data. Another goal is to transform collected data into knowledge useful for increasing effectivity of vascular operations.
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Application for monitoring and analysis of vascular reconstructions
Drozen, Jan ; Hoksza, David (advisor)
Implantation and the care of vascular reconstructions and accesses for haemodialysis is one of areas of cardiovascular surgery. Both vascular reconstructions, known as bypasses, and prosthetic haemodialytic accesses, known as grafts, are used only if conventional therapies are unsuccessful. Thus effectivity of these operations is critically important for patient survival. The aim of this thesis is development of software system for evidence data obtained during vascular operations and following checkups. Important is also support for basic analytical and statistical processing of collected data. Another goal is to transform collected data into knowledge useful for increasing effectivity of vascular operations.
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