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Design of Data Warehouse and Data Structure in BigQuery for Selected Business
Šimková, Michaela ; Kříž, Jiří (oponent) ; Luhan, Jan (vedoucí práce)
This master's thesis focuses on the design and implementation of a data warehouse and data structure in the BigQuery cloud environment, with the aim of analyzing data obtained from Google Analytics 4 and subsequent automation of processing these data and their visual interpretation. The theoretical part of the work presents key concepts and principles related to Business Intelligence, data warehouses, web analytics, and Business Intelligence tools in the cloud environment, thus providing the necessary theoretical basis for the practical part of the work. The practical part deals with the design of the data warehouse structure and a specific design of the logical and conceptual model of the data marketplace and its implementation in BigQuery. It describes the company's requirements, extraction of data from the primary system, creation of SQL queries to obtain historical data, and creation of ETL processes for automated processing of new data. The work also includes visualization of the obtained data using the Looker Studio, resulting in an interactive report allowing visual display of data for easier analysis. The objective of this work is to provide an efficient solution for processing web and application data of the selected company using BigQuery. This will enable the company to gain a better understanding of the acquired data, thereby facilitating strategic and informed decision-making.
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Website Optimization Proposal for the Organization Based on Google Analytics
Sydorenko, Polina ; Matečná, Mária (oponent) ; Luhan, Jan (vedoucí práce)
The Master's thesis focuses on proposing the configuration of a Google Analytics 4 tool for a digital company in Brno. The thesis is divided into three main parts. The first part explores the theoretical foundations of web analytics and its tools. The second part involves analyzing the current state of the company's website analytics tools configuration and conducting a thorough analysis of the website's performance. Finally, the third part presents a proposed solution derived from the analysis of the current state and company’s requirements the application of theoretical concepts discussed throughout the thesis.
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Use of Sequential Pattern Mining in Google Analytics
Viskievič, Gergő ; Šabatka, Pavel (oponent) ; Luhan, Jan (vedoucí práce)
The bachelor thesis focuses on the design and development of an algorithm for sequential pattern mining in Google Analytics 4 data. Presents and analyzes available algorithms for sequential pattern mining. Analyzes the data model and the use of Google Analytics 4. Based on the requirements of business processes, the algorithm is proposed suitable for the expected input data.
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Website Optimization Proposal for the Organization Based on Google Analytics
Sydorenko, Polina ; Matečná, Mária (oponent) ; Luhan, Jan (vedoucí práce)
The Master's thesis focuses on proposing the configuration of a Google Analytics 4 tool for a digital company in Brno. The thesis is divided into three main parts. The first part explores the theoretical foundations of web analytics and its tools. The second part involves analyzing the current state of the company's website analytics tools configuration and conducting a thorough analysis of the website's performance. Finally, the third part presents a proposed solution derived from the analysis of the current state and company’s requirements the application of theoretical concepts discussed throughout the thesis.
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Výběr a implementace analytického nástroje pro elektronický obchod
Coufal, Daniel ; Koch, Miloš (oponent) ; Luhan, Jan (vedoucí práce)
Bakalářská práce se zaměřuje na výběr a implementaci analytického nástroje za účelem měření konkrétních událostí dle vytvořeného návrhu nové analytické strategie, uskutečněnou v rámci vybraného elektronického obchodu. Teoretická část představuje principy a jednotlivé pojmy, které jsou základním stavebním kamenem v dalších částech práce. Analytická část představuje zhodnocení současného stavu, návrh nové analytické strategie a nástroje potřebné k její implementaci. Návrhová část popisuje implementaci této strategie.
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Use of Sequential Pattern Mining in Google Analytics
Viskievič, Gergő ; Šabatka, Pavel (oponent) ; Luhan, Jan (vedoucí práce)
The bachelor thesis focuses on the design and development of an algorithm for sequential pattern mining in Google Analytics 4 data. Presents and analyzes available algorithms for sequential pattern mining. Analyzes the data model and the use of Google Analytics 4. Based on the requirements of business processes, the algorithm is proposed suitable for the expected input data.
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