Valor da tecnologia da informação e sua relação com métricas de desempenho empresarial: o caso de uma multinacional do ramo químico

O cenário globalizado e competitivo impulsiona os avanços tecnológicos e proporciona novas oportunidades para o desenvolvimento de inovações e novas soluções. Neste contexto, o papel da Tecnologia da Informação antes atribuído às atividades mais operacionais evolui para um enfoque mais estratégico e de parceria na criação de vantagem competitiva sustentável e assim, contribui para a geração de valor nos negócios. O aumento nos investimentos de TI nas últimas décadas tem sido acompanhado de questionamentos a respeito de retornos de investimento. Apesar dos diversos trabalhos desenvolvidos na área, há ainda controvérsias a respeito do real valor de TI o que torna o tema ao mesmo tempo desafiador e interessante para ser trabalhado. Neste sentido, este trabalho apresenta um estudo de caso de uma empresa multinacional do ramo químico no Brasil, na qual foi implementado um Sistema de Informação Gerencial, o Business Intelligence. Verificar-se-á se o uso de TI através da ferramenta de BI trouxe benefícios para a Organização. O Modelo simplificado de uso de Tecnologia da Informação em benefícios dos negócios e o Balanced Scorecard foram utilizados para sistematizar e auxiliar a condução do trabalho. Os fundamentos teóricos utilizados na discussão e análise do caso abrangem o Uso de TI, a Gestão de TI, Sistemas de Informação, Benefícios e Valor de TI.

Um método de análise de dados temporais para o Cadastro Territorial Multifinalitário Urbano

Pós-graduação em Ciências Cartográficas - FCT

Bio-inspired enhancement of reputation systems for intelligent environments

Providing security to the emerging field of ambient intelligence will be difficult if we rely only on existing techniques, given their dynamic and heterogeneous nature. Moreover, security demands of these systems are expected to grow, as many applications will require accurate context modeling. In this work we propose an enhancement to the reputation systems traditionally deployed for securing these systems. Different anomaly detectors are combined using the immunological paradigm to optimize reputation system performance in response to evolving security requirements. As an example, the experiments show how a combination of detectors based on unsupervised techniques (self-organizing maps and genetic algorithms) can help to significantly reduce the global response time of the reputation system. The proposed solution offers many benefits: scalability, fast response to adversarial activities, ability to detect unknown attacks, high adaptability, and high ability in detecting and confining attacks. For these reasons, we believe that our solution is capable of coping with the dynamism of ambient intelligence systems and the growing requirements of security demands.

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.

Selecting optimal instantiations of data models - Theory and validation of an ex ante approach

The schema of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. Obtaining quickly the appropriate data increases the likelihood that an organization will make good decisions and respond adeptly to challenges. This research presents and validates a methodology for evaluating, ex ante, the relative desirability of alternative instantiations of a model of data. In contrast to prior research, each instantiation is based on a different formal theory. This research theorizes that the instantiation that yields the lowest weighted average query complexity for a representative sample of information requests is the most desirable instantiation for end-user queries. The theory was validated by an experiment that compared end-user performance using an instantiation of a data structure based on the relational model of data with performance using the corresponding instantiation of the data structure based on the object-relational model of data. Complexity was measured using three different Halstead metrics: program length, difficulty, and effort. For a representative sample of queries, the average complexity using each instantiation was calculated. As theorized, end users querying the instantiation with the lower average complexity made fewer semantic errors, i.e., were more effective at composing queries. (c) 2005 Elsevier B.V. All rights reserved.

Responsive systems:an introduction

This paper introduces responsive systems: systems that are real-time, event-based, or time-dependent. There are a number of trends that are accelerating the adoption of responsive systems: timeliness requirements for business information systems are becoming more prevalent, embedded systems are increasingly integrated into soft real-time command-and-control systems, improved message-oriented middleware is facilitating growth in event-processing applications, and advances in service-oriented and component-based techniques are lowering the costs of developing and deploying responsive applications. The use of responsive systems is illustrated here in two application areas: the defense industry and online gaming. The papers in this special issue of the IBM Systems Journal are then introduced. The paper concludes with a discussion of the key remaining challenges in this area and ideas for further work.

Diagnostic Systems in Medicine as Personal Intellectual Tooling

The standards of diagnostic systems formation in medicine based on modeling expert’s “means of action” in form of illegible trees of solution-making taking into consideration the criteria of credibility and usefulness have been suggested. The fragments of “applied” trees at diagnosing infectious and urological diseases have been considered as well. The possibilities of modern tooling theory usage for decision-making during creation of artificial intelligence systems have been discussed.

Application of the Artificial Intelligence Algorithms for System Analysis of Multi Dimension Physiological Data for Developing Polyparametric Information System of Public Health Diagnostics

The polyparametric intelligence information system for diagnostics human functional state in medicine and public health is developed. The essence of the system consists in polyparametric describing of human functional state with the unified set of physiological parameters and using the polyparametric cognitive model developed as the tool for a system analysis of multitude data and diagnostics of a human functional state. The model is developed on the basis of general principles geometry and symmetry by algorithms of artificial intelligence systems. The architecture of the system is represented. The model allows analyzing traditional signs - absolute values of electrophysiological parameters and new signs generated by the model – relationships of ones. The classification of physiological multidimensional data is made with a transformer of the model. The results are presented to a physician in a form of visual graph – a pattern individual functional state. This graph allows performing clinical syndrome analysis. A level of human functional state is defined in the case of the developed standard (“ideal”) functional state. The complete formalization of results makes it possible to accumulate physiological data and to analyze them by mathematics methods.

ERP-rendszerek a számítási felhőben (cloud computing) - A felhőtechnikával összefüggő új ERP-kiválasztási kritériumok elemzése (ERP systems within cloud – Criteria for selection of ERP systems in a cloud environment)

Néhány éve vonult be a köztudatba a cloud computing fogalom, mely ma már a szakirodalomban és az informatikai alkalmazásokban is egyre nagyobb teret foglal el. Ez az új IT-technológia a számítási felhő számítástechnikai szolgáltatásaihoz kapcsolódó ERP-rendszerek szabványosítását, elterjedését eredményezi. A szerzők cikkükben áttekintést adnak a cloud computing mai helyzetéről és a számítási felhőben működő adatfeldolgozó rendszerekkel (kiemelten ERP) kapcsolatos felhasználói elvárásokról, illetve kezdeti, németországi alkalmazási tapasztalatokról. Külön tárgyalják az ERP-rendszerek új kiválasztási céljait és kritériumait, melyek a felhőkörnyezet speciális lehetőségei miatt alakultak ki. _____ The concept of ‘Cloud’ as an IT notion emerged in the past years and proliferated within the business and IT professional community. The concept of cloud gained awareness both in the professional and scientific literature and in the practice of IT/IS world. The cloud has a profound impact on the Business Information Systems, especially on ERP systems. Indirectly, the cloud leads to a massive standardization on ERP systems and their services. In this paper, the authors provide a literature overview about the current situation of Cloud Computing and the requirements established by end-users against the other data processing facilities and systems, outstandingly the ERP systems. The majority of investigated cases are based on samples from Germany. Furthermore, the initial experiences of application are discussed. Separately, the recent selection objectives and criteria for ERP systems are investigated that came into existence because the appearance of Cloud in the IT environment.

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.

Towards a model for exploring the relationship between managerial decision problems and decision support opportunities

The organisational decision making environment is complex, and decision makers must deal with uncertainty and ambiguity on a continuous basis. Managing and handling decision problems and implementing a solution, requires an understanding of the complexity of the decision domain to the point where the problem and its complexity, as well as the requirements for supporting decision makers, can be described. Research in the Decision Support Systems domain has been extensive over the last thirty years with an emphasis on the development of further technology and better applications on the one hand, and on the other hand, a social approach focusing on understanding what decision making is about and how developers and users should interact. This research project considers a combined approach that endeavours to understand the thinking behind managers’ decision making, as well as their informational and decisional guidance and decision support requirements. This research utilises a cognitive framework, developed in 1985 by Humphreys and Berkeley that juxtaposes the mental processes and ideas of decision problem definition and problem solution that are developed in tandem through cognitive refinement of the problem, based on the analysis and judgement of the decision maker. The framework facilitates the separation of what is essentially a continuous process, into five distinct levels of abstraction of manager’s thinking, and suggests a structure for the underlying cognitive activities. Alter (2004) argues that decision support provides a richer basis than decision support systems, in both practice and research. The constituent literature on decision support, especially in regard to modern high profile systems, including Business Intelligence and Business analytics, can give the impression that all ‘smart’ organisations utilise decision support and data analytics capabilities for all of their key decision making activities. However this empirical investigation indicates a very different reality.