Análisis de los sistemas de información en la productividad de la empresa Belta Ltda.

Los sistemas y la tecnología de información han sido una pieza clave en las organizaciones, estos buscan lograr un equilibrio junto con las estrategias empresariales, ya que de esta manera las empresas estarían en mejores condiciones para enfrentar los desafíos del mercado. (Morantes Leal y Miraidy Elena, 2007)1. Para abordar este tema, hemos decidido realizar un análisis de un sistema de información aplicado en la empresa Belta Ltda. para determinar la relación que existe entre la productividad y el uso de los sistemas empresariales. La información de este análisis está compuesta por 6 capítulos divididos de la siguiente manera: En el primer capítulo se muestra una introducción de los sistemas de información empresarial, la importancia del uso de las tecnologías, además se describe los objetivos de esta investigación, el alcance y vinculación de este proyecto con la línea de investigación de la escuela de administración de la universidad del Rosario. En el segundo capítulo se presenta el marco teórico; la descripción de los tipos de sistemas de información, y las metodologías utilizadas para la evaluación del uso de las tecnologías. Enseguida se describe la metodología utilizada para llevar a cabo esta investigación y las herramientas utilizadas para este caso de estudio en el capítulo tres. En el cuarto capítulo se muestra una descripción de la empresa, el organigrama, el entorno general del negocio, y se desarrolla la aplicación del documento guía; el modelo integral 5d`s, que consiste en realizar diferentes diagnósticos para determinar cómo se encuentra la empresa a nivel interno y externo. Finalmente, según el análisis y resultados obtenidos con esta investigación, se dan unas conclusiones finales y se proponen unas recomendaciones para la empresa en los últimos capítulos.

Design of a unified data with business rules storage model for OLTP and OLAP systems

This paper reviews the literature concerning the practice of using Online Analytical Processing (OLAP) systems to recall information stored by Online Transactional Processing (OLTP) systems. Such a review provides a basis for discussion on the need for the information that are recalled through OLAP systems to maintain the contexts of transactions with the data captured by the respective OLTP system. The paper observes an industry trend involving the use of OLTP systems to process information into data, which are then stored in databases without the business rules that were used to process information and data stored in OLTP databases without associated business rules. This includes the necessitation of a practice, whereby, sets of business rules are used to extract, cleanse, transform and load data from disparate OLTP systems into OLAP databases to support the requirements for complex reporting and analytics. These sets of business rules are usually not the same as business rules used to capture data in particular OLTP systems. The paper argues that, differences between the business rules used to interpret these same data sets, risk gaps in semantics between information captured by OLTP systems and information recalled through OLAP systems. Literature concerning the modeling of business transaction information as facts with context as part of the modelling of information systems were reviewed to identify design trends that are contributing to the design quality of OLTP and OLAP systems. The paper then argues that; the quality of OLTP and OLAP systems design has a critical dependency on the capture of facts with associated context, encoding facts with contexts into data with business rules, storage and sourcing of data with business rules, decoding data with business rules into the facts with the context and recall of facts with associated contexts. The paper proposes UBIRQ, a design model to aid the co-design of data with business rules storage for OLTP and OLAP purposes. The proposed design model provides the opportunity for the implementation and use of multi-purpose databases, and business rules stores for OLTP and OLAP systems. Such implementations would enable the use of OLTP systems to record and store data with executions of business rules, which will allow for the use of OLTP and OLAP systems to query data with business rules used to capture the data. Thereby ensuring information recalled via OLAP systems preserves the contexts of transactions as per the data captured by the respective OLTP system.

The effects of normalisation on the ability of business end-users to detect data anomalies: An experimental evaluation

With the proliferation of relational database programs for PC's and other platforms, many business end-users are creating, maintaining, and querying their own databases. More importantly, business end-users use the output of these queries as the basis for operational, tactical, and strategic decisions. Inaccurate data reduce the expected quality of these decisions. Implementing various input validation controls, including higher levels of normalisation, can reduce the number of data anomalies entering the databases. Even in well-maintained databases, however, data anomalies will still accumulate. To improve the quality of data, databases can be queried periodically to locate and correct anomalies. This paper reports the results of two experiments that investigated the effects of different data structures on business end-users' abilities to detect data anomalies in a relational database. The results demonstrate that both unnormalised and higher levels of normalisation lower the effectiveness and efficiency of queries relative to the first normal form. First normal form databases appear to provide the most effective and efficient data structure for business end-users formulating queries to detect data anomalies.

Data mining languages for business intelligence

Doctoral Thesis in Information Systems and Technologies Area of Engineering and Manag ement Information Systems

Information flow analysis using data-dependent logical propositions

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Sustainability of systems interoperability in dynamic business networks

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores

Pervasive business intelligence: a marketing intelligence framework proposal

Doctoral Thesis in Information Systems and Technologies Area of Information Systems and Technology

Information and Material Flows in Project Business

Tavoitteena diplomityössä oli kuvata projektiliiketoimintaa harjoittavan yrityksen informaatio- ja materiaalivirrat toimitusprojekteissa. Selvitys haluttiin tehdä tulevia kehitysprojekteja varten. Diplomityö toteutettiin kahessa osassa: laatimalla aiheeseen liittyvä teoriakatsaus ja kartoittamalla todellinen tilanne yrityksen sisällä.Teoriaosassa kuvattiin tarkastelualue ja projektiliiketoiminnan erityispiirteitä sekä käsiteltiin tietojärjestelmiä ja materiaalivirran hallintaan liittyviä asioita. Yrityksen informaatio- ja materiaalivirtojen nykytila kartoitettiin laatimalla vuokaaviot kolmen esimerkkituotteen toimitusprojekteista. Kaaviot laadittiin yrityksen sisäisten dokumenttien ja kvalitatiivisten haastattelujen pohjalta. Kaavioiden sisältöä täydennettiin taulukoimalla kaavioissa esiintyvien dokumettien sisältöä. Työn tuloksena muodostui kuva tiedonkäsittelyn nykytilasta myynti- ja toimitusprojekteissa, pelkistetty visio tulevaisuuden tietojärjestelmien rooleista sekä ehdotuksia tulevia kehitysprojekteja varten.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

Benchmarking or business opportunity: Using milk recording data to expose your clients' weaknesses

Routine milk recording data, often covering many years, are available for approximately half the dairy herds of England and Wales. In addition to milk yield and quality, these data include production events that can be used to derive objective Key Performance Indicators (KPI) describing a herd's fertility and production. Recent developments in information systems give veterinarians and other technical advisers access to these KPIs on-line. In addition to reviewing individual herd performance, advisers can establish local benchmark groups to demonstrate the relative performance of similar herds in the vicinity. The use of existing milk recording data places no additional demands on farmer's time or resources. These developments could also readily be exploited by universities to introduce veterinary undergraduates to the realities of commercial dairy production.

Evolving features-algorithms knowledge map to support NIDS data intelligence and learning loop architecting – a generalised approach to NIDS pattern feature space knowledge processing

This paper describes a proposed new approach to the Computer Network Security Intrusion Detection Systems (NIDS) application domain knowledge processing focused on a topic map technology-enabled representation of features of the threat pattern space as well as the knowledge of situated efficacy of alternative candidate algorithms for pattern recognition within the NIDS domain. Thus an integrative knowledge representation framework for virtualisation, data intelligence and learning loop architecting in the NIDS domain is described together with specific aspects of its deployment.

Towards the design of a unified semantics model for OLTP and OLAP systems

The concepts of on-line transactional processing (OLTP) and on-line analytical processing (OLAP) are often confused with the technologies or models that are used to design transactional and analytics based information systems. This in some way has contributed to existence of gaps between the semantics in information captured during transactional processing and information stored for analytical use. In this paper, we propose the use of a unified semantics design model, as a solution to help bridge the semantic gaps between data captured by OLTP systems and the information provided by OLAP systems. The central focus of this design approach is on enabling business intelligence using not just data, but data with context.

The Brazilian Seismographic Integrated Systems (BRASIS): Infrastructure and data management

In geophysics and seismology, raw data need to be processed to generate useful information that can be turned into knowledge by researchers. The number of sensors that are acquiring raw data is increasing rapidly. Without good data management systems, more time can be spent in querying and preparing datasets for analyses than in acquiring raw data. Also, a lot of good quality data acquired at great effort can be lost forever if they are not correctly stored. Local and international cooperation will probably be reduced, and a lot of data will never become scientific knowledge. For this reason, the Seismological Laboratory of the Institute of Astronomy, Geophysics and Atmospheric Sciences at the University of São Paulo (IAG-USP) has concentrated fully on its data management system. This report describes the efforts of the IAG-USP to set up a seismology data management system to facilitate local and international cooperation. © 2011 by the Istituto Nazionale di Geofisica e Vulcanologia. All rights reserved.

The Influence of Enterprise Systems on Business and Information Technology

Business strategy is important to all organizations. Nearly all Fortune 500 firms are implementing Enterprise Resource Planning (ERP) systems to improve the execution of their business strategy and to improve integration with its information technology (IT) strategy. Successful implementation of these multi-million dollar software systems are requiring new emphasis on change management and on Business and IT strategic alignment. This paper examines business and IT strategic alignment and seeks to explore whether an ERP implementation can drive business process reengineering and business and IT strategic alignment. An overview of business strategy and strategic alignment are followed by an analysis of ERP. The “As-Is/To-Be” process model is then presented and explained as a simple, but vital tool for improving business strategy, strategic alignment, and ERP implementation success.