Monitorización inteligente de redes de comunicación

El avance tecnológico de los últimos años ha aumentado la necesidad de guardar enormes cantidades de datos de forma masiva, llegando a una situación de desorden en el proceso de almacenamiento de datos, a su desactualización y a complicar su análisis. Esta situación causó un gran interés para las organizaciones en la búsqueda de un enfoque para obtener información relevante de estos grandes almacenes de datos. Surge así lo que se define como inteligencia de negocio, un conjunto de herramientas, procedimientos y estrategias para llevar a cabo la “extracción de conocimiento”, término con el que se refiere comúnmente a la extracción de información útil para la propia organización. Concretamente en este proyecto, se ha utilizado el enfoque Knowledge Discovery in Databases (KDD), que permite lograr la identificación de patrones y un manejo eficiente de las anomalías que puedan aparecer en una red de comunicaciones. Este enfoque comprende desde la selección de los datos primarios hasta su análisis final para la determinación de patrones. El núcleo de todo el enfoque KDD es la minería de datos, que contiene la tecnología necesaria para la identificación de los patrones mencionados y la extracción de conocimiento. Para ello, se utilizará la herramienta RapidMiner en su versión libre y gratuita, debido a que es más completa y de manejo más sencillo que otras herramientas como KNIME o WEKA. La gestión de una red engloba todo el proceso de despliegue y mantenimiento. Es en este procedimiento donde se recogen y monitorizan todas las anomalías ocasionadas en la red, las cuales pueden almacenarse en un repositorio. El objetivo de este proyecto es realizar un planteamiento teórico y varios experimentos que permitan identificar patrones en registros de anomalías de red. Se ha estudiado el repositorio de MAWI Lab, en el que se han almacenado anomalías diarias. Se trata de buscar indicios característicos anuales detectando patrones. Los diferentes experimentos y procedimientos de este estudio pretenden demostrar la utilidad de la inteligencia de negocio a la hora de extraer información a partir de un almacén de datos masivo, para su posterior análisis o futuros estudios. ABSTRACT. The technological progresses in the recent years required to store a big amount of information in repositories. This information is often in disorder, outdated and needs a complex analysis. This situation has caused a relevant interest in investigating methodologies to obtain important information from these huge data stores. Business intelligence was born as a set of tools, procedures and strategies to implement the "knowledge extraction". Specifically in this project, Knowledge Discovery in Databases (KDD) approach has been used. KDD is one of the most important processes of business intelligence to achieve the identification of patterns and the efficient management of the anomalies in a communications network. This approach includes all necessary stages from the selection of the raw data until the analysis to determine the patterns. The core process of the whole KDD approach is the Data Mining process, which analyzes the information needed to identify the patterns and to extract the knowledge. In this project we use the RapidMiner tool to carry out the Data Mining process, because this tool has more features and is easier to use than other tools like WEKA or KNIME. Network management includes the deployment, supervision and maintenance tasks. Network management process is where all anomalies are collected, monitored, and can be stored in a repository. The goal of this project is to construct a theoretical approach, to implement a prototype and to carry out several experiments that allow identifying patterns in some anomalies records. MAWI Lab repository has been selected to be studied, which contains daily anomalies. The different experiments show the utility of the business intelligence to extract information from big data warehouse.

Estudio de patrones de interacción entre los estudiantes y la Plataforma de Tele-Enseñanza en la UPM

Vivimos en una sociedad en la que la información ha adquirido una vital importancia. El uso de Internet y el desarrollo de nuevos sistemas de la información han generado un ferviente interés tanto de empresas como de instituciones en la búsqueda de nuevos patrones que les proporcione la clave del éxito. La Analítica de Negocio reúne un conjunto de herramientas, estrategias y técnicas orientadas a la explotación de la información con el objetivo de crear conocimiento útil dentro de un marco de trabajo y facilitar la optimización de los recursos tanto de empresas como de instituciones. El presente proyecto se enmarca en lo que se conoce como Gestión Educativa. Se aplicará una arquitectura y modelo de trabajo similar a lo que se ha venido haciendo en los últimos años en el entorno empresarial con la Inteligencia de Negocio. Con esta variante, se pretende mejorar la calidad de la enseñanza, agilizar las decisiones dentro de la institución académica, fortalecer las capacidades del cuerpo docente y en definitiva favorecer el aprendizaje del alumnado. Para lograr el objetivo se ha decidido seguir las etapas del Knowledge Discovery in Databases (KDD), una de las metodologías más conocidas dentro de la Inteligencia de Negocio, que describe el procedimiento que va desde la selección de la información y su carga en sistemas de almacenamiento, hasta la aplicación de técnicas de minería de datos para la obtención nuevo conocimiento. Los estudios se realizan a partir de la información de la activad de los usuarios dentro la plataforma de Tele-Enseñanza de la Universidad Politécnica de Madrid (Moodle). Se desarrollan trabajos de extracción y preprocesado de la base de datos en crudo y se aplican técnicas de minería de datos. En la aplicación de técnicas de minería de datos, uno de los factores más importantes a tener en cuenta es el tipo de información que se va a tratar. Por este motivo, se trabaja con la Minería de Datos Educativa, en inglés, Educational Data Mining (EDM) que consiste en la aplicación de técnicas de minería optimizadas para la información que se genera en entornos educativos. Dentro de las posibilidades que ofrece el EDM, se ha decidido centrar los estudios en lo que se conoce como analítica predictiva. El objetivo fundamental es conocer la influencia que tienen las interacciones alumno-plataforma en las calificaciones finales y descubrir nuevas reglas que describan comportamientos que faciliten al profesorado discriminar si un estudiante va a aprobar o suspender la asignatura, de tal forma que se puedan tomar medidas que mejoren su rendimiento. Toda la información tratada en el presente proyecto ha sido previamente anonimizada para evitar cualquier tipo de intromisión que atente contra la privacidad de los elementos participantes en el estudio. ABSTRACT. We live in a society dominated by data. The use of the Internet accompanied by developments in information systems has generated a sustained interest among companies and institutions to discover new patterns to succeed in their business ventures. Business Analytics (BA) combines tools, strategies and techniques focused on exploiting the available information, to optimize resources and create useful insight. The current project is framed under Educational Management. A Business Intelligence (BI) architecture and business models taught up to date will be applied with the aim to accelerate the decision-making in academic institutions, strengthen teacher´s skills and ultimately improve the quality of teaching and learning. The best way to achieve this is to follow the Knowledge Discovery in Databases (KDD), one of the best-known methodologies in B.I. This process describes data preparation, selection, and cleansing through to the application of purely Data Mining Techniques in order to incorporate prior knowledge on data sets and interpret accurate solutions from the observed results. The studies will be performed using the information extracted from the Universidad Politécnica de Madrid Learning Management System (LMS), Moodle. The stored data is based on the user-platform interaction. The raw data will be extracted and pre-processed and afterwards, Data Mining Techniques will be applied. One of the crucial factors in the application of Data Mining Techniques is the kind of information that will be processed. For this reason, a new Data Mining perspective will be taken, called Educational Data Mining (EDM). EDM consists of the application of Data Mining Techniques but optimized for the raw data generated by the educational environment. Within EDM, we have decided to drive our research on what is called Predictive Analysis. The main purpose is to understand the influence of the user-platform interactions in the final grades of students and discover new patterns that explain their behaviours. This could allow teachers to intervene ahead of a student passing or failing, in such a way an action could be taken to improve the student performance. All the information processed has been previously anonymized to avoid the invasion of privacy.

Autogestor de contenidos dinámico (ACD)

Este proyecto se centra en la construcción de una herramienta para la gestión de contenidos de muy diversos tipos, siendo fácilmente adaptable a cada uno de los contextos. Permite guardar los contenidos necesarios gracias a un formulario previamente personalizado, de este modo hay un editor que se dedica solamente a la introducción de los contenidos y un administrador que personaliza los campos del formulario según los contenidos. En esencia la herramienta sirve de apoyo a dos tipos de usuario, desarrolladores (administrador) y redactores (editor), a los primeros les simplifica las tareas de conceptualización de las estructuras de datos de las que se desea tener persistencia y sirve como base para construir los editores que usan los redactores, por otro lado proporciona un API sencillo, potente y ágil para recuperar los datos introducidos por los redactores. La herramienta a su vez está pensada para ser interoperable, es decir, no obliga a usar un tipo de almacenamiento persistente concreto. Puede utilizar desde los sencillos archivos de texto, con lo que puede desplegarse en servidores treméndamente básicos. Por otro lado, si se necesita potencia en las búsquedas, nada debe impedir el uso de bases de datos relacionales como MySql. O incluso si se quiere dar un paso más y se quiere aprovechar la flexibilidad, potencia y maleabilidad de las bases de datos NoSql (como MongoDB) no es costoso, lo que hay que hacer es implementar una nueva clase de tipo PersistentManager y desarrollar los tipos de búsqueda y recuperación de contenidos que se necesiten. En la versión inicial de la herramienta se han implementado estos tres tipos de almacenes, nada impide usar sólo alguno de ellos y desechar el resto o implementar uno nuevo. Desde el punto de vista de los redactores, les ofrece un entorno sencillo y potente para poder realizar las tareas típicas denominadas CRUD (Create Read Update Delete, Crear Leer Actualizar y Borrar), un redactor podrá crear, buscar, re-aprovechar e incluso planificar publicación de contenidos en el tiempo. ABSTRACT This project focuses on building a tool for content management of many types, being easily adaptable to each context. Saves the necessary content through a previously designed form, thus there will be an editor working only on the introduction of the contents and there will be an administrator to customize the form fields as contents. Essentially the tool provides support for two types of users, developers (administrator) and editors, the first will have simplified the tasks of conceptualization of data structures which are desired to be persistent and serve as the basis for building the structures that will be used by editors, on the other hand provides a simple, powerful and agile API to retrieve the data entered by the editors. The tool must also be designed to be interoperable, which means not to be bound by the use of a particular type of persistent storage. You can use simple text files, which can be deployed in extremely basic servers. On the other hand, if power is needed in searches, nothing should prevent the use of relational databases such as MySQL. Or even if you want to go a step further and want to take advantage of the flexibility, power and malleability of NoSQL databases (such as MongoDB) it will not be difficult, you will only need to implement a new class of PersistentManager type and develop the type of search and query of content as needed. In the initial version of the tool these three types of storage have been implemented, it will be entitled to use only one of them and discard the rest or implement a new one. From the point of view of the editors, it offers a simple and powerful environment to perform the typical tasks called CRUD (Create Read Update Delete), an editor can create, search, re-use and even plan publishing content in time.

Enrichment of the Phenotypic and Genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Currently there are an overwhelming number of scientific publications in Life Sciences, especially in Genetics and Biotechnology. This huge amount of information is structured in corporate Data Warehouses (DW) or in Biological Databases (e.g. UniProt, RCSB Protein Data Bank, CEREALAB or GenBank), whose main drawback is its cost of updating that makes it obsolete easily. However, these Databases are the main tool for enterprises when they want to update their internal information, for example when a plant breeder enterprise needs to enrich its genetic information (internal structured Database) with recently discovered genes related to specific phenotypic traits (external unstructured data) in order to choose the desired parentals for breeding programs. In this paper, we propose to complement the internal information with external data from the Web using Question Answering (QA) techniques. We go a step further by providing a complete framework for integrating unstructured and structured information by combining traditional Databases and DW architectures with QA systems. The great advantage of our framework is that decision makers can compare instantaneously internal data with external data from competitors, thereby allowing taking quick strategic decisions based on richer data.

Novas tendências, o big data: deteção de fraudes e transações no comércio local: SAF-T com tecnologia big data

Dissertação apresentada à Escola Superior de Tecnologia do Instituto Politécnico de Castelo Branco para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Desenvolvimento de Software e Sistemas Interactivos, realizada sob a orientação científica da categoria profissional do orientador Doutor Eurico Ribeiro Lopes, do Instituto Politécnico de Castelo Branco.

Managerialism at the bottom of the pyramid: a case study in Brazil

Nas últimas décadas, a Base da Pirâmide tem sido cada vez mais debatida entre líderes ocidentais como a nova terra das oportunidades. Com o advento do neoliberalismo no campo do desenvolvimento na década de 1990, o papel da sociedade civil e, em particular, o de Organizações Não-Governamentais, passou a ser enfatizado como sendo central nas estratégias ocidentais no "Sul" do mundo. Os atores do desenvolvimento, no entanto, muitas vezes abordaram essas questões utilizando perspectivas tradicionais, que estavam geralmente fora de contexto. A tese foca na controvérsia em torno do uso de técnicas de gestão em cenários que diferem daqueles nos quais estas ferramentas têm sido desenvolvidas. Em particular, ela procura compreender em que medida o gerencialismo - a ideologia da gestão - está a influenciando as atividades de uma Organização Não-Governamental brasileira, a Galpão Aplauso. O estudo, usando uma estrutura teórica, analisa o relacionamento entre a ONG e seus parceiros, sublinhando os resultados de conflitos ideológicos. No geral, descobriu-se como o encontro das perspectivas do Norte e do Sul originou alguns debates que levaram, em parte, à aceitação de ideias gerencialistas, tais como a replicabilidade e sistematização de processos, enquanto que em alguns casos, eles intensificaram a resistência da ONG sobre conceitos como sustentabilidade financeira e transformação em um negócio social.

A COMUNICAÇÃO COMO UM PROCESSO DE INTELIGÊNCIA EMPRESARIAL EM PLANEJAMENTO ESTRATÉGICO

Esta tese trata da comunicação como instrumento de inteligência empresarial numa instituição de ensino superior. Ela pretende demonstrar que a comunicação agrega vantagem competitiva às organizações que atuam no mercado educacional. O presente trabalho se fundamenta em referenciais teóricos das ciências da Comunicação e de Planejamento Estratégico, e seus procedimentos metodológicos incluem, além de revisão bibliográfica extensiva e análise de documentos, a técnica da observação participante, com o acompanhamento das atividades do grupo de trabalho intitulado Comunicação e Integração entre os anos 2003 e 2005, que integrava o Planejamento Estratégico da UMESP Universidade Metodista de São Paulo. Ao final do trabalho, buscou-se mapear as condições necessárias para que a comunicação se constitua efetivamente num processo de inteligência empresarial, incorporando-se à gestão estratégica das organizações. Admitimos que a Comunicação Empresarial ainda tem de vencer alguns desafios e que eles, necessariamente, não são fáceis de serem superados. É necessário considerar sempre que a Comunicação Empresarial não flui no vazio, não se realiza à margem das organizações, mas está umbilicalmente associada a um particular sistema de gestão, a uma específica cultura organizacional e que é expressão, portanto, de uma realidade concreta. Para que a Comunicação Empresarial seja assumida como estratégica, essa condição deverá ser favorecida pela gestão, pela cultura e mesmo pela alocação adequada de recursos (humanos, tecnológicos e financeiros), pois sem os quais ela não se realiza. Logo, se estes pressupostos não estiverem devidamente satisfeitos, será prematuro concluir pelo caráter estratégico da Comunicação Empresarial. Mais ainda: a comunicação não será estratégica em função unicamente do trabalho mais ou menos competente dos profissionais de comunicação. Há exigências outras que, infelizmente, fogem ao seu controle. Em resumo, nesse trabalho são analisadas três questões centrais. A primeira delas diz respeito ao conceito de estratégia. A segunda refere-se ao chamado ethos organizacional em que se insere a prática comunicacional. Finalmente, são examinadas as condições básicas para que a comunicação estratégica realmente prevaleça.

Моделирование Многомерных Данных в Системе METAS BI-Platform

Представлено формальное описание многомерной модели данных, реализованной в программном комплексе METAS BI-Platform. В статью включено описание объектов многомерной модели (измерений и множеств измерений и т.д.), их свойств и организации, а также операций, выполняемых над ними. Описаны методы агрегации многомерных данных, позволяющие эффективно агрегировать массивы числовых показателей. Программный комплекс METAS BI-Platform предназначен для многомерного анализа данных, получаемых из гетерогенных источников, и позволяет упростить разработку BI-приложений. Программный комплекс представляет собой многоуровневое приложение с архитектурой «Клиент-сервер». Каждый уровень комплекса соответствует степени абстракции данных. На самом низком уровне расположены драйверы доступа к специфическим физическим источникам данных. Следующий уровень – уровень виртуальной СУБД, позволяющей осуществлять унифицированный доступ к данным, что избавляет от необходимости учитывать специфику конкретных СУБД при разработке BI-приложений. Реализован программный интерфейс комплекса (API). В распоряжение разработчиков предоставляется набор готовых компонентов, которые могут быть использованы при создании BI-приложений. Это позволяет разрабатывать на основе комплекса BI-приложения, отвечающие современным требованиям, предъявляемым к подобным системам.

The role of individualism and collectivism as predictors of attributions for unethical work behavior: An empirical examination across two culturally diverse groups

This dissertation addresses how the cultural dimensions of individualism and collectivism affect the attributions people make for unethical behavior at work. The moderating effect of ethnicity is also examined by considering two culturally diverse groups: Hispanics and Anglos. The sample for this study is a group of business graduate students from two universities in the Southeast. A 20-minute survey was distributed to master's degree students at their classroom and later on returned to the researcher. Individualism and collectivism were operationalized as by a set of attitude items, while unethical work behavior was introduced in the form of hypothetical descriptions or scenarios. Data analysis employed multiple group confirmatory factor analysis for both independent and dependent variables, and subsequently multiple group LISREL models, in order to test predictions. Results confirmed the expected link between cultural variables and attribution responses, although the role of independent variables shifted, due to the moderating effect of ethnicity, and to the nuances of each particular situation. ^

Team diversity and leadership: Tests of model of process and direct effects

A model was tested to examine relationships among leadership behaviors, team diversity, and team process measures with team performance and satisfaction at both the team and leader-member levels of analysis. Relationships between leadership behavior and team demographic and cognitive diversity were hypothesized to have both direct effects on organizational outcomes as well as indirect effects through team processes. Leader member differences were investigated to determine the effects of leader-member diversity leader-member exchange quality, individual effectiveness and satisfaction.^ Leadership had little direct effect on team performance, but several strong positive indirect effects through team processes. Demographic Diversity had no impact on team processes, directly impacted only one performance measure, and moderated the leadership to team process relationship.^ Cognitive Diversity had a number of direct and indirect effects on team performance, the net effects uniformly positive, and did not moderate the leadership to team process relationship.^ In sum, the team model suggests a complex combination of leadership behaviors positively impacting team processes, demographic diversity having little impact on team process or performance, cognitive diversity having a positive net impact impact, and team processes having mixed effects on team outcomes.^ At the leader-member level, leadership behaviors were a strong predictor of Leader-Member Exchange (LMX) quality. Leader-member demographic and cognitive dissimilarity were each predictors of LMX quality, but failed to moderate the leader behavior to LMX quality relationship. LMX quality was strongly and positively related to self reported effectiveness and satisfaction.^ The study makes several contributions to the literature. First, it explicitly links leadership and team diversity. Second, demographic and cognitive diversity are conceptualized as distinct and multi-faceted constructs. Third, a methodology for creating an index of categorical demographic and interval cognitive measures is provided so that diversity can be measured in a holistic conjoint fashion. Fourth, the study simultaneously investigates the impact of diversity at the team and leader-member levels of analyses. Fifth, insights into the moderating impact of different forms of team diversity on the leadership to team process relationship are provided. Sixth, this study incorporates a wide range of objective and independent measures to provide a 360$\sp\circ$ assessment of team performance. ^

Self-other rating discrepancy and personality antecedents

This study explored individual difference factors to help explain the discrepancy that has been found to exist between self and other ratings in prior research. Particularly, personality characteristics of the self-rater were researched in the current study as a potential antecedent for self-other rating agreement. Self, peer, and supervisor ratings were provided for global performance as well as five competencies specific to the organization being examined. Four rating tendency categories, over-raters, under-raters, in-agreement (good), and in-agreement (poor), established in research by Atwater and Yammarino were used as the basis of the current research. The sample for rating comparisons within the current study consisted of 283 self and supervisor dyads and 275 for self and peer dyads from a large financial organization. Measures included a custom multi-rater performance instrument and the personality survey instrument, ASSESS, which measures 20 specific personality characteristics. MANCOVAs were then performed on this data to examine if specific personality characteristics significantly distinguished the four rating tendency groups. Examination of all personality dimensions and overall performance uncovered significant findings among rating groups for self-supervisor rating comparisons but not for self-peer rating comparisons. Examination of specific personality dimensions for self-supervisory ratings group comparisons and overall performance showed Detail Interest to be an important characteristic among the hypothesized variables. For self-supervisor rating comparisons and specific competencies, support was found for the hypothesized personality dimension of Fact-based Thinking which distinguished the four rating groups for the competency, Builds Relationships. For both self-supervisor and self-peer rating comparisons, the competencies, Builds Relationships and Leads in a Learning Environment, were found to have significant relationship with several personality characteristics, however, these relationships were not consistent with the hypotheses in the current study. Several unhypothesized personality dimensions were also found to distinguish rating groups for both self-supervisor and self-peer comparisons on overall performance and various competencies. Results of the current study hold implications for the training and development session that occur after a 360-degree evaluation process. Particularly, it is suggested that feedback sessions may be designed according to particular rating tendencies to maximize the interpretation, acceptance and use of evaluation information. ^

A retrospective-longitudinal examination of the relationship between apportionment of seat time in community-college algebra courses and student academic performance

During the past decade, there has been a dramatic increase by postsecondary institutions in providing academic programs and course offerings in a multitude of formats and venues (Biemiller, 2009; Kucsera & Zimmaro, 2010; Lang, 2009; Mangan, 2008). Strategies pertaining to reapportionment of course-delivery seat time have been a major facet of these institutional initiatives; most notably, within many open-door 2-year colleges. Often, these enrollment-management decisions are driven by the desire to increase market-share, optimize the usage of finite facility capacity, and contain costs, especially during these economically turbulent times. So, while enrollments have surged to the point where nearly one in three 18-to-24 year-old U.S. undergraduates are community college students (Pew Research Center, 2009), graduation rates, on average, still remain distressingly low (Complete College America, 2011). Among the learning-theory constructs related to seat-time reapportionment efforts is the cognitive phenomenon commonly referred to as the spacing effect, the degree to which learning is enhanced by a series of shorter, separated sessions as opposed to fewer, more massed episodes. This ex post facto study explored whether seat time in a postsecondary developmental-level algebra course is significantly related to: course success; course-enrollment persistence; and, longitudinally, the time to successfully complete a general-education-level mathematics course. Hierarchical logistic regression and discrete-time survival analysis were used to perform a multi-level, multivariable analysis of a student cohort (N = 3,284) enrolled at a large, multi-campus, urban community college. The subjects were retrospectively tracked over a 2-year longitudinal period. The study found that students in long seat-time classes tended to withdraw earlier and more often than did their peers in short seat-time classes (p < .05). Additionally, a model comprised of nine statistically significant covariates (all with p-values less than .01) was constructed. However, no longitudinal seat-time group differences were detected nor was there sufficient statistical evidence to conclude that seat time was predictive of developmental-level course success. A principal aim of this study was to demonstrate—to educational leaders, researchers, and institutional-research/business-intelligence professionals—the advantages and computational practicability of survival analysis, an underused but more powerful way to investigate changes in students over time.

Progettazione e Sviluppo di un Sistema di Proactive Alerting all'interno di una piattaforma di Big Data Analytics

Il lavoro presentato in questo elaborato tratterà lo sviluppo di un sistema di alerting che consenta di monitorare proattivamente una o più sorgenti dati aziendali, segnalando le eventuali condizioni di irregolarità rilevate; questo verrà incluso all'interno di sistemi già esistenti dedicati all'analisi dei dati e alla pianificazione, ovvero i cosiddetti Decision Support Systems. Un sistema di supporto alle decisioni è in grado di fornire chiare informazioni per tutta la gestione dell'impresa, misurandone le performance e fornendo proiezioni sugli andamenti futuri. Questi sistemi vengono catalogati all'interno del più ampio ambito della Business Intelligence, che sottintende l'insieme di metodologie in grado di trasformare i dati di business in informazioni utili al processo decisionale. L'intero lavoro di tesi è stato svolto durante un periodo di tirocinio svolto presso Iconsulting S.p.A., IT System Integrator bolognese specializzato principalmente nello sviluppo di progetti di Business Intelligence, Enterprise Data Warehouse e Corporate Performance Management. Il software che verrà illustrato in questo elaborato è stato realizzato per essere collocato all'interno di un contesto più ampio, per rispondere ai requisiti di un cliente multinazionale leader nel settore della telefonia mobile e fissa.

Informationsförvaltning inom en stor organisation : En fallstudie på Trafikverket

Denna studie syftar till att undersöka hur en stor organisation arbetar med förvaltning av information genom att undersöka dess nuvarande informationsförvaltning, samt undersöka eventuella förslag till framtida informationsförvaltning. Vidare syftar studien också till att undersöka hur en stor organisation kan etablera en tydlig styrning, samverkan, hantering och ansvars- och rollfördelning kring informationsförvaltning. Denna studie är kvalitativ, där datainsamlingen sker genom dokumentstudier och intervjuer. Studien bedrivs med abduktion och är en normativ fallstudie då studiens mål är att ge vägledning och föreslå åtgärder till det fall som uppdragsgivaren har bett mig att studera. Fallet i denna studie är ett typiskt fall, då studiens resultat kan vara i intresse för fler än studiens uppdragsgivare, exempelvis organisationer med liknande informationsmiljö. För att samla teori till studien så har jag genomfört litteraturstudier om ämnen som är relevanta för studiens syfte: Informationsförvaltning, Business Intelligence, Data Warehouse och dess arkitektur, samt Business Intelligence Competency Center. Denna studie bidrar med praktiskt kunskapsbidrag, då studien ger svar på praktiska problem. Uppdragsgivaren har haft praktiska problem i och med en icke fungerade informationsförvaltning, och denna studie har bidragit med förslag på framtida informationsförvaltning. Förslaget på framtida informationsförvaltning involverar ett centraliserat Data Warehouse, samt utvecklingen utav en verksamhet som hanterar informationsförvaltning och styrningen kring informationsförvaltningen inom hela organisationen.

Decisions, decisions everywhere (in the open data era).

Abstract: Decision support systems have been widely used for years in companies to gain insights from internal data, thus making successful decisions. Lately, thanks to the increasing availability of open data, these systems are also integrating open data to enrich decision making process with external data. On the other hand, within an open-data scenario, decision support systems can be also useful to decide which data should be opened, not only by considering technical or legal constraints, but other requirements, such as "reusing potential" of data. In this talk, we focus on both issues: (i) open data for decision making, and (ii) decision making for opening data. We will first briefly comment some research problems regarding using open data for decision making. Then, we will give an outline of a novel decision-making approach (based on how open data is being actually used in open-source projects hosted in Github) for supporting open data publication. Bio of the speaker: Jose-Norberto Mazón holds a PhD from the University of Alicante (Spain). He is head of the "Cátedra Telefónica" on Big Data and coordinator of the Computing degree at the University of Alicante. He is also member of the WaKe research group at the University of Alicante. His research work focuses on open data management, data integration and business intelligence within "big data" scenarios, and their application to the tourism domain (smart tourism destinations). He has published his research in international journals, such as Decision Support Systems, Information Sciences, Data & Knowledge Engineering or ACM Transaction on the Web. Finally, he is involved in the open data project in the University of Alicante, including its open data portal at http://datos.ua.es