In recent years, Business Intelligence is one of the fastest growing software industry according to foreign analyzes. More and more companies realize the importance of tools for Business Intelligence and dashboarding. That is why I chose this topic for my thesis. The main part of this thesis focuses on study support for subject 4IT314 Enterprise Information Systems. This course teaches student how to work with the ERP system Microsoft Dynamics AX. The main shortage of this subject is the lack of feedback to students. Therefore it was decide to integrate BI tools that will be used for dashboarding over database of Microsoft Dynamics AX. In the theoretical part are explains the basic terms essential to understanding BI and dashboarding. On the basis of defined criteria was chose BI tool for integration in to the subject 4IT314. In the practical part of this thesis is described the implementation of this tool and created user documentation, which is used as study materials for students.

Throughout last decades, knowledge discovery from databases as one of the information and communicaiton technologies' disciplines has developed into its current state being showed increasing interest not only by major business corporates. Presented diploma thesis deals with problematique of data mining while paying prime attention to its practical utilization within business environment. Thesis objective is to review possibilities of data mining applications and to decompose implementation techniques focusing on specific data mining methods and algorithms as well as adaptation of business processes. This objective is subject of theoretical part of thesis focusing on principles of data mining, knowledge discovery from databases process, data mining commonly used methods and algorithms and finally tasks typically implemented in this domain. Further objective consists in presenting data mining benefits on the model example that is being displayed in the practical part of the thesis. Besides created data mining models evalution, practical part contains also design of subsequent steps that would enable higher efficiency in some specific areas of given business. I believe previous point together with characterization of knowledge discovery in databases process to be considered as the most beneficial one's of the thesis.

Business analytics refers to the skills, technologies, applications and practisies for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods. Business intelligence traditionally focuses on using a consistent set of metrics to both measure past performance and guide business planning, which is also based on data and statistical methods. Analytics makes extensive use of data, statistical or quantitative analyses, explanatory and predictive modeling, and fact based management to drive decision, making. Analytics may be used as input for human decisions or may drive fully automated decisions. In other words, querying, reporting, OLAP, and alert tools can answer questions such as what happened, how many, how often, where the problem is, and what actions are needed. Business analytics can answer questions like why is this happening, what if these trends continue, what will happen next, what is the best that can happen (optimize). Example of application analytics in different areas: banks use data analyses to differentiate among customers based on credit risk, usage of other characteristics with appropriate product offering. Harrah's company (from 2010 renamed and called Caesers entertaiment. Gaming corporation that owns and operate over 50 casinos, hotels, and seven golf courses under several brands), uses analytics for customer loyalty programs. Deere & Company (manufacturer of agricultural machinery like tractors, combine harvesters, sprayers and other) saved more than $1 billion by employing and implementing a new analytical tool to better optimize inventory. We can mention areas where within analytics are basic domain model: sales/retail business, financial services, risk & credit, marketing, fraud, pricing, telecommunications, supply chain, transportation and many others.

The subject of the thesis is the proof of concept of Business Intelligence (BI) implementation in the Communications service department from the Kapsch BusinessCom s.r.o. company. The aim of the work is developing a BI proof solution and consequently producing an output for the final users. The main outcome of the thesis is operating BI solutions used in practice. The solution was carried out using tools MS SQL Server 2008 R2 Management Studio, MS SQL Server 2008 R2 Business Intelligence Development studio and MS Excel 2007. The project analyses the data obtained from the ERP (Enterprise Resource Planning) database acquired from the MS Dynamics Navision system. Information on "Voice" projects from the Communications service department, which mainly focuses on the service of PBXs and similar products, are recorded in the project among others. A multidimensional analysis was carried out, data warehouse was designed, data pumps were created, OLAP (On-line Analytical Processing) block and output in the Microsoft Excel 2007 program were carried out during the project.

The topic of this master thesis is the application of BI (Business Intelligence) Solutions in the insurance industry. The main objectives are the creation of model analyses and the design and implementation of partial BI solutions on the QlikView platform for smaller non-life insurance companies. The model also takes into consideration aspects of the new EU insurance regulatory directive, Solvency II, by selecting input parameters needed for the calculation of premium and reserve risk using segmentation rules from the lines of business specified in the directive. The thesis consists of three main parts. The first focuses on the QlikView BI platform, its market place, architecture, SW components and the technologies it takes advantage of. It also examines the differences and specific aspects of developing a BI solution using QlikView, compared to other more traditional platforms - one of these aspects is associative data modeling. The second part of the thesis focuses on the financial risks that insurance companies are exposed to, methods for their quantification and techniques that are used for solvency determination -- based upon Solvency II guidelines -- using SCR (Solvency Capital Requirement) and MCR (Minimum Capital Requirement) indicators. Particular chapters explain the concept behind the Solvency II directives and demonstrate the structure of standard formulae used for SCR calculations, which are used for ascertaining the Premium and/or Reserve risk. The final part of the thesis builds upon the earlier sections and contains practical instructions and recommendations for the development of BI solutions based on the QlikView platform in smaller non-life insurance companies. A designed model of the BI application can primarily be used for basic corporate performance monitoring but can also assist in the partial calculation of some risk categories according to the Solvency II directives. The practical section -- which is the ultimate product and the main benefit of this master thesis -- expands beyond the theory to provide a basic conceptual framework for the development of BI applications in small insurance company environments.

The specialization of the final master thesis is theory and a practical view of Location Intelligence. The author is writing about specific parts of development of the application which is focused on analysis of consumer's behaviour for managers of retail businesses focused on customer's satisfaction. The application is a new way of researching consumer's behaviour. Spatial data is connected with the subject of research -- analysis of the movement of consumers in retail stores. The application is a practical tool for better targeting for managers or marketing specialists. The app was developed by four researcher Martin Matějka, Tomáš Rosenberger, Vilém Kalus (three diploma researchers) and Ondřej Funiok. The Main goal of the final thesis was to describe the application from the business point of view and to design layout of the user interface. The business model helped us to specify the application from the business point of view. We reached the main goal with research articles of Location Intelligence. The thesis contains theory basis of informatics and geo-informatics field, Business Intelligence, Location Intelligence and selected business models. The practical part of the thesis is composed of integrating application to the business model, functionality description. From functionality description we designed the user interface. The practical part closes with the use case of application in Vysoká škola ekonomická v Praze. Benefits of the thesis are in development of real, new application for future commercial use. Contribution to the theory of Location Intelligence and analytical solution of development of user interface.

Pesquisas em várias partes do mundo vêm sendo realizadas para compreender os fatores que interferem no sucesso internacional do Esporte de Alto Rendimento (EAR). Neste contexto, a Gestão da Informação (GI) torna-se estratégica para que as organizações do esporte possam usufruir dos dados e dos processos que envolvem o sucesso na gestão esportiva. Contudo, pouco foi desenvolvido para estabelecer modelos de gestão de informações que monitorem continuamente a situação do EAR brasileiro. Diante disso, o objetivo deste estudo é construir um modelo para a gestão de informações do EAR no Brasil. Por meio de um misto de métodos, o estudo foi constituído por quatro fases: (1) levantamento e análise dos métodos de sistematização de informações do esporte- para identificar os elementos fundamentais para o sucesso esportivo e para revisar os métodos de sistematização de informações do EAR; (2) estudo piloto – para desenvolver o método de coleta, catalogação e sistematização das informações do EAR no Brasil; (3) construção do modelo de gestão de informações do EAR utilizando um modelo entidaderelacionamento (MER) para gestão informatizada dos dados; (4) validação do modelo de gestão, por meio do julgamento de um comitê de especialistas. Os resultados revelaram que em 29 nações já foram desenvolvidos estudos para sistematizar informações do esporte e conhecer os elementos que interferem no sucesso do EAR. O estudo do escopo desses elementos resultou na seleção de dez dimensões para coleta e catalogação de informações do EAR brasileiro em um Banco de Dados (BD) MySQL, modelado com o objetivo de permitir a articulação entre as dimensões Com a eliminação das redundâncias e a construção do MER, a padronização e categorização dos termos permitiram a construção de um modelo de gestão de informações do EAR que possibilita a atualização continuada das dimensões e informações mapeadas, composto por oito dimensões: Recursos Financeiros; Infraestrutura Esportiva; Equipamentos e Materiais Esportivos; Entidades e Governança; Atletas e Profissionais do Esporte; Eventos e Resultados Esportivos; Ciência e Tecnologia; Legislação. O modelo utiliza os princípios do Business Intelligence (BI) e um banco de dados que pode ser continuamente adaptado a fatores, contextos e a esportes diferentes. É um repositório digital de informações composto por 75 tabelas divididas em nove conjuntos que são articulados por meio de 185 relacionamentos, permitindo realizar análises, produzir relatórios e indicadores de forma intra ou interdimensional e uni ou multiesporte. Este modelo permite cruzamentos e apresentação de respostas simultâneas a partir de informações de atletas, de entidades, de esportes, suas provas e de dados que envolvem o financiamento, a infraestrutura e demais dimensões. Concluiu-se que este estudo inova ao utilizar os fatores de sucesso para estabelecer um modelo informatizado de gestão de informações do EAR, que pode ser implementado em um país ou em uma entidade. Ao inserir a inteligência de negócios na gestão esportiva, o trabalho concede as informações mais importantes para a tomada de decisão de gestores, podendo qualificar as políticas e contribuir para uma comunicação eficiente entre as diferentes entidades ligadas ao esporte. / Researches in various parts of the world are being conducted to understand the factors that interfere in the international success of Elite Sports (ES). In this context, the Information Management (IM) becomes strategic so that the sports organizations can take advantage of the data and the processes that involve the success in sport management. However, little was developed to establish information management models that continuously monitor the Brazilian ES. The objective of this study, therefore, is to construct a model for the management of ES information in Brazil. Through a combination of methods, the study consisted of four phases: (1) survey and analysis of methods to systematize of sport information - to identify the fundamental elements for sports success and to review the methods to systematize information of the ES; (2) pilot study - to develop the method of collecting, cataloging and systematizing ES information in Brazil; (3) construction of the ES information management model using an entity-relationship model (ERM) for computerized management of sports data; (4) validation of the management model, through the judgment of an experts committee. The results revealed that in 29 nations studies have been developed to systematize sport information and to know the elements that interfere in the success of the ES. The study of the scope of these elements resulted in the selection of ten dimensions for collecting and cataloging Brazilian ES information in a MySQL Database (DB), modeled with the objective of allowing the articulation between the dimensions The elimination of redundancies and the construction of the ERM, the standardization and categorization of the terms allowed the construction of an information management model of the ES that allows continuous updating dimensions and information mapped, composed of eight dimensions: Financial Resources; Sports Infrastructure; Sports Materials; Entities and Governance; Athletes and Sport Professionals; Events and Sport Results; Science and Technology; Legislation. The model uses the principles of Business Intelligence (BI) and a database that can be continuously adapted to different factors, contexts, and sports. It is a digital repository of information composed of 75 tables, divided into nine sets that are articulated through 185 relationships, allowing to produce analyzes, reports and indicators of intra or interdimensional form and uni or multisport. This model allows information crossing and presentation of simultaneous responses of athletes, entities, sports, their evidence and data that involve financing, infrastructure, and other dimensions. It was concluded that this study innovates when using the success factors to establish a computerized information management model of the ES, which can be implemented in a country or an entity. By inserting business intelligence into sports management, this work provides the most important information for decision-making by managers, can qualify the policies and contribute to efficient communication between different sports entities.

Data warehousing provides organizations with strategic tools to achieve the competitive advantage that organazations are constantly seeking. The use of tools such as data mining, indexing and summaries enables management to retrieve information and perform thorough analysis, planning and forcasting to meet the changes in the market environment. in addition, The data warehouse is providing security measures that, if properly implemented and planned, are helping organizations ensure that their data quality and validity remain intact.

Business Intelligence (BI) hjälper organisationer att kunna nå sina mål genom ett mer effektivt beslutsfattande. Ny teknik kommer ständigt och att tillämpa Cloud Computing (CC) tillsammans med BI ger många fördelar. Detta är väldigt ny teknologi som har en låg mognadsnivå men ständigt utvecklas och i denna rapport kan du läsa om den funktionalitet som finns tillgänglig om du väljer att använda dig av CC för att utföra BI. Det har utförts intervjuer för samla in kvalitativ data som kan beskriva detta fenomen för att kunna ge organisationer mer insikt i hur detta fungerar. Genom att utföra semistrukturerade intervjuer med mycket rum för diskussion har många intressanta mönster framtagits. Totalt deltog fyra stycken respondenter som arbetat eller arbetar med BI och erfarenhet inom CC. Resultatet fokuserar på att ge förslag och ideer till en organisation som kan tänka sig välja en CC lösning för att utföra BI. Mognadsnivån för denna ny teknologi är fortfarande väldigt låg och användningsområden och datatyper samt visualiserings funktioner kommer att tas upp.

This study presents perceptions towards non-relational, or just NoSQL, databases in IT- and Business Intelligence companies, where we try to determine the need for NoSQL databases in these areas. Earlier studies indicate that the rise of Big Data will force companies to sooner or later expand their data storages to be able to handle the vast amount of data that will emerge, and to find ways to easily manage it. With this in mind, we wanted to determine why some Business Intelligence-companies still had not implemented non-relational databases in their systems, what this would implicate and how necessary it actually is. Our study included a case study at a Business Intelligence-company that still had not adopted these relatively new kinds of databases. First we used a survey to get an idea of what kind of knowledge concerning NoSQL-databases the employees at the company actually had, and to help us create questions for the interviews that would be the next step in our study. Through the interviews we had with three consultants and two developers we gathered a lot of interesting data concerning the company’s attitude towards implementing alternative databases in the system as a complement to their current SQL-based databases. For example, the low level of knowledge about NoSQL-databases of the employees showed a lot of preconceptions and assumptions about these alternative databases, that by extension led to a very skeptical attitude towards them. We learned however that the employees, especially the consultants, worried about the growing amount of data, which already was becoming laborious, and we estimate that companies that has not adopted a solution for this will eventually reach an inflection point where the amount of data will exceed the company’s ability to handle it. / <p>På grund av rådande pandemi (covid-19) hölls Studentkonferens Examensarbete i informatik 2020 genom videokonferens (Zoom)</p>