The thesis focuses on the application of Business Intelligence technologies in the insurance area, aiming concretely at their use in insurance companies. The aim is to introduce and summarize the various processes and information needs that are part of an insurance company and the ways that business intelligence tools can support and improve those processes. To achieve this goal I describe and present the internal functioning of the main processes in insurance companies emphasizing on data examples and the concrete use of BI. Furthermore, I point out two specific examples of Business Intelligence products, which are built and are aimed for the insurance industry. Specifically, I review InsFocus Business Intelligence product from InsFocus Insurance and SAS Business Intelligence from SAS. These two products are reviewed in terms of architecture, functionality and implementation process. At the end of the thesis, I've created a theoretical analysis for a Business Intelligence implementation in a fictitious insurance company. The benefit of this work is to present a comprehensive look at the advantages of Business Intelligence for insurance companies, at some specific products which relate to BI and insurance, and a look at the way that an analysis for a BI insurance solution is made.

Thesis maps the situation in the telecommunications market in the Czech Republic, analyzes the major players on the Czech nad world market, and analyzes the possibilities of marketing and presentation of high-tech to customers in user-friendly form.

Stocker de grandes quantités de données complexifie les interactions avec les systèmes de Business Intelligence (BI). Les systèmes de recommandation semblent un choix logique pour aider les utilisateurs dans leur analyse. Ils extraient des comportements de données historiques et suggèrent des actions personnalisées, potentiellement redondantes, via des scores de similarité. La diversité est essentielle pour améliorer la satisfaction des utilisateurs, d’où l’intérêt particulier accordé aux recommandations complémentaires. Nous avons étudié deux problèmes concrets d’exploration de données en BI et proposons de découvrir et exploiter les intentions utilisateur pour fournir deux recommandeurs de requête. Le premier, un recommandeur collaboratif réactif original basé sur l’intention, recommande des séquences de requêtes à l’utilisateur pour poursuivre son analyse. Le second propose proactivement un ensemble de requêtes pour compléter un rapport BI, en fonction di contexte utilisateur. / The storage of big amounts of data may lead to a series of long questions towards the expected solution which complicates user interactions with Business Intelligence (BI) systems. Recommender systems appear as a natural solution to help the users complete their analysis. They try to discover user behaviors from the past logs and to suggest personalized actions by predicting lists of likeness scores, which may lead to redundant recommendations. Nowadays, diversity is becoming essential to improve users’ satisfaction, thus, a special interest is dedicated to complementary recommendation. We studied two concrete data exploration problems in BI and we propose to discover and leverage the user intents to provide two query recommenders. The first, an original reactive collaborative Intent-based Recommender, recommends sequences of queries for the user to pursue her analysis. The second one proactively proposes a bundle of queries to complete user BI report, based on the user intents.

The current business environment is rapidly and fundamentally changing. The main driver are digital technologies. Companies face the pressure to exploit those technologies to improve their business processes in order to achieve competitive advantage. In the light of increased complexity of business processes and the existence of corporate Big Data stored in information systems, the discipline of process mining has emerged. Investigate how process mining can support the optimization of business processes. In this qualitative study, an illustrative case study research is utilized involving eight research participants. Hereby, data is primarily collected from semi-structured interviews. The data is analyzed using content analysis. In addition, the illustrative case serves the purpose to demonstrate the application of process mining. The research revealed that process mining has important impacts on current business process improvement. Not all of them were explicitly positive. The derived success factors should support vendors, current and potential users to apply process mining safe and successfully.

Business Intelligence (BI) syftar till att förädla data för att förbättra det organisatoriska beslutsfattandet. Bristande datakvalité orsakar många misslyckade BI-projekt och studier belyser att säkerställande av data av hög kvalité är grundläggande för att lyckas inom BI. Uppsatsens syfte var därför att skapa en förståelse av praktiska tillvägagångssätt för en sådan säkerställning. Begreppet datakvalité kan brytas ner i dimensioner för att göra det mer hanterbart, och denna studie bygger på vad som tidigare tagits fram som nyckeldimensioner. Intervjuer genomfördes med fyra konsulter med expertis och lång erfarenhet inom BI. Utöver en effektiv ETL-process och kontroller i BI-systemet, genomsyras resultatet av ett behov av förarbete inför lagring i källsystemen samt kontinuerliga avstämningsrutiner. Detta för att möjliggöra säkerställandet av data av hög kvalité i större utsträckning. Indikationer ges även på att tillvägagångssätt för att säkerställa data av hög kvalité styrs av de krav som ställs på datat för att det ska vara användbart för dess avsedda syfte.

Em um momento em que a produção de conhecimento é cada vez mais necessária junto à contínua expansão e diversificação dos meios de hospedagem, torna-se interessante investigar o recém-criado campo de Inteligência de Negócios ou Business Intelligence (BI). Na hotelaria, as tecnologias e os sistemas de informação são empregados em diversas áreas, como gestão, política de preços, programação e operação de sistemas de informações estratégicas, a fim de facilitar as análises dos principais indicadores de desempenho do setor. A preocupação gira em torno da elevada quantidade de informações produzidas, sendo fundamental dispor de uma maior precisão em processos de tomada de decisões. Nesse contexto, propõe-se um estudo com enfoque no tema Inovação em gestão hoteleira no Brasil, com o objetivo geral de analisar a gestão da inteligência de negócios das redes hoteleiras que atuam no Brasil. Trata-se de uma pesquisa de caráter qualitativo, baseado em revisão de literatura e aplicação de questionários junto aos gestores das redes hoteleiras, podendo, assim, mapear as necessidades das cadeias hoteleiras em termos de gestão, ao se avaliar as práticas de BI. Como resultados, foram identificados os principais softwares de BI existentes no mercado brasileiro (Cognos, MicroStrategy, SAS, Business Objects, Oracle Business Intelligence, QlikView e Pentaho) e os mais adequados para cada porte de empresa. Também foram identificadas as soluções utilizadas para a gestão da informação de BI pelas redes: emprego de softwares de BI, terceirização por meio de serviços de consultoria e tratamento manual dos dados dos sistemas dos hotéis. Por fim, foram avaliados os resultados da gestão de BI nas redes, concluindo que a implantação de gestão de BI considerando a gestão da informação atrelada às TIs traz mais benefícios do que custos às redes hoteleiras analisadas, sobretudo no que diz respeito a propiciar uma tomada de decisão mais acertada / In a time when the production of knowledge is increasingly required for the continued expansion and diversification of lodging facilities, it is interesting to investigate the newly created Intelligence field of Business or Business Intelligence (BI). In hospitality, technology and information systems are used in various fields such as management, pricing, scheduling and operation of strategic information systems to facilitate analysis of key industry performance indicators. The concern revolves around the vast amount of information produced and it is essential to dispose of greater accuracy in decision-making processes. In this context, is proposing a study focusing on the theme Innovation in hotel management in Brazil, with the overall objective to analyse the management of the business intelligence of the chains operating in Brazil. It is a qualitative research, based on literature review and application of questionnaires with the managers of the chains, and thus can map the needs of hotel chains regarding management when evaluating BI practices. As a result, the primary existing BI software in the Brazilian market was identified (Cognos, MicroStrategy, SAS, Business Objects, Oracle Business Intelligence, QlikView, and Pentaho) and the most suitable for every size company. Also, the solutions identified were used for the management of BI information across networks: use of BI software, outsourcing through consultancy and manual data processing systems of the hotel services. Finally, it was evaluated the BI management achievements in the nets, concluding that the BI management implementation - considering the information management linked to IT - bring more benefits than costs to the analysed chains, particularly about providing a more positive decision making

Para Rud (2009, p.3) o objetivo primordial do Business Intelligence é fornecer a informação certa para a pessoa adequada, dentro do tempo esperado e no formato correto, através do canal mais apropriado. Para cumprir este complexo desafio, Eckerson (2009, p.4) afirma que a questão central está em compreender quais as ferramentas e métodos são mais adequados para os diferentes grupos de usuários que usufruem das soluções analíticas. Assim, esta obra procura dar continuidade às observações de Eckerson (2009, p.4), aprofundando o entendimento dos usuários analíticos e de seu relacionamento com as ferramentas de BI disponíveis, avaliando uma nova variável: o estilo cognitivo dos usuários. Em outras palavras, procura avaliar se existe uma relação entre os estilos cognitivos dos usuários analíticos (representados neste caso pelos tipos psicológicos) e sua escolha por determinadas funcionalidades disponíveis em aplicações de Business Intelligence (como, por exemplo, painéis de informação, relatórios pré-configurados, relatórios ad hoc, relatórios OLAP, modelos preditivos e mineração de dados), além de outros aspectos relacionados com esta associação. No Estudo de Caso realizado com o Banco Alfa, as opiniões em relação a este assunto são variadas e parecem ser influenciadas pelo nível hierárquico do respondente; contudo, indicam a existência de alguma influência ainda que difícil de ser quantificada ou explicada. Por outro lado, no limitado levantamento executado com alguns usuários - cujos dados colhidos são avaliados com a ajuda do Teste Qui-Quadrado e do Teste Exato de Fischer, não é possível constatar a influência. De qualquer forma, mais do que negar de forma conclusiva a existência da relação, os resultados parecem indicar que uma das variáveis pode ser aprimorada, abrindo uma possibilidade de desenvolvendo para esta análise. / Rud (2009, p.3) states that the primary goal of Business Intelligence is to provide the accurate information to the right person within the expected timeframe and proper format, through the most suitable channel. To fulfill this complex challenge, Eckerson (2009, p.4) affirms that the key issue is to understand which tools and methods are the most suitable for the different groups of users who benefit from analytical applications. The key objective of this thesis is to continue the studies and observations of Eckerson (2009, p.4), understanding BI users and their relationship with these tools, investigating a new variable: the users\' cognitive style. In other words, this thesis details the effort to verify if there is a relationship between cognitive styles (represented in this case by psychological types) of analytical users and their choice and preference for certain functionalities available in Business Intelligence applications (such as, dashboards, formatted reports, ad hoc reports, OLAP reports, predictive modeling and data mining), as well as other aspects of this association. In the Case Study conducted with Bank Alfa, the opinions on this matter are diverse and seem to be influenced by the hierarchical level of the respondent; however, they seem to indicate the existence of some influence even though it is difficult to quantify or explain. On the other hand, on the limited survey carry out with some BI users - the collected data was evaluated with Chi-Square Test and Fisher\'s Exact Test, is not possible to identify the influence. Nevertheless, instead of rejecting any type of relationship, the results indicate that one of the variables should be further improved and studied.

Les données ont toujours été un atout clé pour beaucoup d’industries et d’entreprises ;cependant, ces derniers temps les possesseurs de données jouissent d’un véritable avantage compétitif sur les autres. De nos jours, les compagnies collectent de gros volumes de données et les stockent dans de grandes bases de données multidimensionnelles appelées entrepôts de données. Un entrepôt de données présente les données agrégées sous la forme d’un cube dont les cellules contiennent des faits et des informations contextuelles telles que des dates, des lieux, des informations sur les clients et fournisseurs, etc. Les solutions d’entreposage de données utilisent avec succès OLAP (Traitement Analytique En Ligne – en anglais Online Analytical Processing) afin d’analyser ces grands ensembles de données ;par exemple, les informations des ventes peuvent être agrégées selon le lieu et/ou la dimension temporelle. Les tendances récentes des technologies et du Web posent actuellement de nouveaux défis. Une bonne quantité de l’information disponible sur le Web s’y trouve sous une forme qui se prête au traitement par machine (Web Sémantique) ;les outils de veille économique (en anglais Business Intelligence ou BI) doivent être capables de découvrir et récupérer les informations pertinentes, et les présenter aux utilisateurs afin de les assister dans une bonne analyse de la situation. De nombreux gouvernements et organisations rendent leurs données publiquement accessible, identifiables avec des URI (Unified Resource Identifiers), et les lient à d’autres données. Cette collection de jeux de données interconnectés sur le Web s’appelle Linked Data [1]. Ces jeux de données sont basés sur le modèle RDF (Resource Description Framework) – un format standard pour l’échange de données sur le Web [2]. SPARQL, un protocole et un langage de requêtes pour RDF [4], est utilisé pour interroger et manipuler les jeux de données RDF stockés dans des triplestores SPARQL. SPARQL 1.1 Federated Query [6] définit également une extension pour exécuter des requêtes distribuées sur plusieurs triplestores. Le standard actuel permet donc des requêtes analytiques complexes sur de multiples sources de données, et l’intégration de ces données dans le processus d’analyse devient une nécessité pour les outils de BI. Cependant, en raison de la quantité et de la complexité des données disponibles sur le Web, leur incorporation et leur utilisation ne sont pas toujours évidentes. Par conséquent, une solution OLAP efficace sur des source Web Sémantiques est nécessaire pour améliorer les outils de BI. Cette thèse de doctorat se concentre sur les défis liés à l’optimisation des requêtes analytiques qui utilisent des données provenant de plusieurs triplestores SPARQL. Premièrement, cette thèse propose un framework pour la découverte, l’intégration et l’interrogation analytique des Linked Data – ce type d’OLAP a été nommé OLAP Exploratoire [21]. Ce framework est conçu pour utiliser un schéma multidimensionnel du cube OLAP exprimé dans des vocabulaires RDF, afin de pouvoir interroger des sources de données, extraire et agréger des données, et construire un cube de données. Nous proposons également un processus assisté par ordinateur pour découvrir des sources de données précédemment inconnues et construire un schéma multidimensionnel du cube. Deuxièmement, vu l’inefficacité actuelle des triplestores SPARQL pour l’exécution des requêtes analytiques fédérées, cette thèse propose un ensemble de stratégies pour le traitement de ces requêtes ainsi qu’un module (appelé Cost-based Optimizer for Distributed Aggregate ou CoDA) pour optimiser leur exécution. Troisièmement, afin de surmonter les défis liés aux techniques de traitement des requêtes SPARQL agrégées sur un seul triplestore, nous proposons MARVEL (MAterialized Rdf Views with Entailment and incompLeteness) – une approche qui utilise des techniques de vues matérialisées spécifiques à RDF pour traiter les requêtes agrégées complexes. Notre approche consiste en un algorithme de sélection de vues selon un modèle de coût associé spécifique à RDF, une syntaxe pour la définition des vues et un algorithme pour la réécriture des requêtes SPARQL en utilisant les vues matérialisées RDF. Finalement, nous nous concentrons sur les techniques relatives au support des requêtes analytiques SPARQL sur des données liées situées en de multiples triplestores, qui nous conduisent à d’intéressantes analyses et constatations à grande échelle. En particulier, la technique proposée est capable d’intégrer les schémas divers des endpoints SPARQL, donnant accès aux données via des hiérarchies dans le style d’OLAP pour permettre des analyses uniformes, efficaces et puissantes. Enfin, cette thèse préconise une plus grande attention au traitement des requêtes analytiques au sein des systèmes RDF distribués. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Syftet med denna kandidatuppsats är att, via kvalitativa intervjuer, identifiera och beskriva ett landstings process för hur patient- och sjukvårdsdata, genom olika typer av dataanalyser, kan generera rättidiga beslut.   I det valda kvalitativa tillvägagångssättet skapades en semi-strukturerad intervjuguide, baserad på en analysmodell. Fem intervjuer med anställda inom fallstudieorganisationen genomfördes. För att underlätta för respondenterna och ge en tydlig helhetssyn på intervjuns innehåll, fick respondenterna innan intervjun se analysmodellen som skapats.   Deskriptiv analys är den vanligaste dataanalysmodellen som används av respondenterna, i form av verksamhets- och produktionsuppföljning. Det framgår även i undersökningen att det är viktigt med ett brett dataunderlag för beslutsfattning och att Landstinget i Värmland överlag är en mycket faktabaserad organisation. Förutsättningarna för att kunna fatta rättidiga beslut, genererade från dataanalyser, anses vara att veta vilka frågeställningar som ska besvaras, att data snabbt finns tillgänglig och att analyser utförs på denna tillgängliga data. Men även om data snabbt finns tillgängligt för beslutsfattarna och analyser gjorts, medför inte det rättidiga beslut. Data ger inte alltid en korrekt eller sann bild, utan behöver först tolkas innan besluten kan fattas. Tolkningar av data kan skilja sig åt vilket medför att ytterligare en person behöver titta på materialet, vilket också medför att besluten skjuts fram. Det anses även saknas ett enhetligt arbetssätt för hur de anställda arbetar i vårdsystemen.   Rättidiga beslut finns på olika nivåer inom landstinget. När det gäller den övergripande nivån är det inte brådskande med beslut, men ju mer operativt personalen arbetar desto viktigare är det med snabba beslut. Detta visar att ”rättidiga beslut” har olika betydelser, beroende på var i verksamheten de anställda befinner sig. Vården är tidspressad och det är inte alltid det finns möjlighet att analysera de data som finns tillräckligt mycket.

As organizações estão expostas a uma quantidade e variabilidade cada vez mais crescente de informações. A capacidade de se antecipar às tendências e se adequar ao ambiente passa a ser, além de fonte de vantagem competitiva, fator necessário para a sobrevivência. Nessa realidade, organizações frequentemente apresentam dificuldades de leitura de seu ambiente e adaptação ao meio. Acredita-se na necessidade de desenvolvimento de uma capacidade interna da organização para que o monitoramento do ambiente se estabeleça, bem como análise de oportunidades, planejamento de ações de melhoria e reconfiguração da organização. Este estudo buscou verificar a relação da Inteligência - enquanto processo de monitoramento do ambiente - como uma Capacidades Dinâmica, e de como esta pode contribuir com a geração de vantagem competitiva. Criou-se um modelo de pesquisa, utilizando-se dos modelos de Rios (2010) e Teece (2014), relacionando os conceitos de Inteligência e Capacidade Dinâmicas, e estas com a Vantagem Competitiva. Por meio de um questionário, realizou-se uma Pesquisa Survey, onde coletaram-se respostas de funcionários e/ou sócio de empresas brasileiras, independente de porte ou segmento. Para análise, utilizou-se da Modelagem de Equações Estruturais, e foi possível demonstrar que a Inteligência influencia positivamente nas Capacidades Dinâmicas do sub-grupo Transforming, na Estratégia e na Vantagem Competitiva. Dessa forma o modelo desenvolvido, tendo apresentado boa confiabilidade e aderência, pode também ser validado. / Organizations are exposed to an increasing amount and variability of information. The ability to anticipate trends and adapt to the environment becomes, besides a source of competitive advantage, a necessary factor for survival. In this reality, organizations frequently present difficulties in reading their environment and adapting to them. We believe in the need to develop an internal capacity of the organization for the monitoring of the environment to be established, as well as analysis of opportunities, planning of actions of improvement and reconfiguration of the organization. This study sought to verify the relationship of Intelligence - as a process of monitoring the environment - as a Dynamic Capabilities, and how this can contribute to the generation of competitive advantage. A research model was created, using the models of Rios (2010) and Teece (2014), relating the concepts of Dynamic Intelligence and Capacity, and these with the Competitive Advantage. By means of a questionnaire, a Survey Research was conducted, where responses were collected from employees and / or partners of Brazilian companies, regardless of size or segment. For the analysis, it was used the Modeling of Structural Equations, and it was possible to demonstrate that the Intelligence influences positively in the Dynamic Capacities of the Transforming subgroup, in the Strategy and the Competitive Advantage. In this way the developed model, having presented good reliability and adhesion, can also be validated.