Examinando por Materia "Big data"
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Ítem Analítica de datos : un estudio de caso de su uso para identificar riesgos estratégicos en grandes compañías de Medellín(2019) Coronado Medina, Luis Alejandro; Núñez Patiño, María Antonia; Rodrígues Taborda; EduardoThis research seeks to describe how, from the implementation of data analytics tools, large companies in Medellín are transforming strategic risk management from their identification stage, to respond to changes in their business ecosystem. A qualitative methodology was followed with a descriptive exploratory scope, through semi-structured interviews with risk management leaders. The obtained results demonstrate the importance that companies attach to the implementation of data analytics to identify strategic risks. The recognition of the relevance of these new tools is based on a greater possibility of carrying out a more complex, more accurate, efficient and more objective analysis of the environment, that increasingly involve more variables and that are able to establish greater connections between them.Ítem Caoba y los cazadores de datos en EAFIT(Universidad EAFIT, 2020-07-25) Higuita Posada, Santiago; ColaboradorÍtem El conocimiento es poder entendiendo la correlación entre la información recolectada a través de un perfil de Instagram y el consumo de contenido de forma periódica y repetitiva en dicha plataforma(Universidad EAFIT, 2020) Rieder Monsalve, Paulina; Toro Valencia, Jose AlbertoLife in the XXI century happens trought Internet, and more specifically, trought social media. This plataforms attract users attention by costumization of content, wich is constructed from the knowledge extracted in the data mining process thanks to the personal data that every user yields with the use of the service. The purpose of personalization is the augmentation of time spent online thus, the amount of personal data given. This data is the fundamental asset to digital economy. Due to the wide knowledge derived from data mining and the profound social incertion that social media has, users get trapped onto a asimetric power relationship with the companies that provide this service wich directly impacts rights such as privacy. Even though privacy has international and national regulations, its guideline is not appropiate to face the current challenges.Ítem Education 4.0: a view from different digital proposals(Medellín : Editorial Eafit, 2020) Montoya-Múnera, Edwin; Aguilar, José; Monsalve-Pulido, Julián Alberto; Salazar, Camilo; Varela-Tabares, Daniela; Jiménez-Narváez, Marvin; Montoya-Jaramillo, Edwin; Tabares, Marta S.; Vallejo, Paola; Vega, Juan Sebastián; Nieto, Agustín; Córdoba, Camilo; Gil, Guillermo Alejandro; Trefftz, Helmuth; Esteban, Pedro Vicente; fonedit@eafit.edu.co; Suárez-Giraldo, Cristian; Caicedo Alarcón, ÓscarThis book is, then, a way to expose some research projects undertaken at the EAFIT University, in agreement with several technological companies, that develop three perspectives about education in a digital context, in which the informatic mediation and the use of technologies 4.0 lead the revision of the teaching and learning processes through a novel perspective. Together, this book presents how 4.0 technologies enable a highly participatory and dialogic education, where students of different levels have the possibility of learning and training in their discipline while developing soft skills and, at the same time, the teachers can follow the development and evolution of these capacities and the purposes expected in the courses. Given the variety of courses modalities that are currently offered (e-learning, b-learning, m-learning, u-learning, among others), the applications presented in each chapter, as well as the appropriation of technologies for the enrichment of the students’ cognitive and social skills, are an opportunity to explore new perspectives and approaches to Education 4.0Ítem A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs(Springer Verlag, 2019-10-01) Peña A.; Bonet I.; Lochmuller C.; Tabares M.S.; Peña A.; Bonet I.; Lochmuller C.; Tabares M.S.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las ComunicacionesAdvances in technology and an increase in the amount and complexity of data that are generated in healthcare have led to an indispensable revolution in this sector related to big data. Analytics of information based on multimodal clinical data sources requires big data projects. When starting big data projects in the healthcare sector, it is often necessary to assess the maturity of an organization with respect to big data, i.e., its capacity in managing big data. The assessment of the maturity of an organization requires multicriteria decision making as there is no single criterion or dimension that defines the maturity level regarding big data but an entire set of them. Based on the ISO 15504, this article proposes a fuzzy ELECTRE structure methodology to assess the maturity level of small- and medium-sized enterprises in the healthcare sector. The obtained experimental results provide evidence that this methodology helps to determine and compare maturity levels in big data management of organizations or the evolution of maturity over time. This is also useful in terms of diagnosing the readiness of an organization before starting to implement big data initiatives or technologies. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.Ítem Informe académico de indicadores de coyuntura bancaria en Colombia : caso de estudio modelado en Power BI(Universidad EAFIT, 2019) Tavera Londoño, Idaly; Restrepo Tobón,Diego Alexander;71785909The objective of this research is to generate academic indicators of banking situation for Colombia. This report will serve as input to the banking and finance research group of Eafit, providing data of interest for the decision making of students, graduates and entrepreneurs and will be published in the university financial laboratory. The methodology used in this research is self-learning in Power BI, for the automation, transformations and application of visualizations of bank indicators. The main contribution of the bank account indicators report is that users can have information available in one place, without having to visit several pages to gather all the data.Ítem Monitoring of machining in the cloud as a cost management service and follow of cutting parameters: Environment developed with IoT tools(IGI Global, 2019-01-01) Giraldo-Castrillon F.-A.; Páramo-Bermúdez G.-J.; Muñoz-Betancur J.-M.; Giraldo-Castrillon F.-A.; Páramo-Bermúdez G.-J.; Muñoz-Betancur J.-M.; Universidad EAFIT. Departamento de Ingeniería de Producción; Grupo en Tecnologías para la ProducciónThe present work developed an environment in the cloud with IoT tools for the intelligent monitoring of cutting processes in a three-axis CNC machine. To achieve it, a group of sensors incorporated into the machine are connected to a data acquisition card in charge of sending the measurements delivered by the sensors to the IoT environment in the cloud. The data received was processed in real-time, and at the end of the machining, an automatic report was generated that includes: the cost of the operation, total process time, average energy consumption in watts, and positions of the X, Y, Z axes in function of time. The findings of this study bypass production managers from developing a processes sheet, reducing fabrication time, and increasing productivity. The architecture of the system was put to the test raising two case studies, which demonstrate the relevance and the significant impact of the platform in the new era of digital manufacturing. © 2019, IGI Global.Ítem ¿Quién domina a las serpientes? Big Data vs Habeas Data : riesgos y límites(Universidad EAFIT, 2022) Isaza Marín, Larry Alexis; Toro Valencia, José AlbertoÍtem Retos para la regulación del big data y la inteligencia artificial : privacidad, democracia y derechos humanos(Universidad Eafit, 2020) Trujillo Agudelo, Ana María; Barboza Vergara, Antonio CarlosÍtem Revisión de literatura de macrodatos(Universidad EAFIT, 2019) Ramírez Aristizábal, Sebastián; Uribe De Correa, Beatriz AmparoBig data is a subject that has gained prominence in the last time. The term refers to an information management model that uses voluminous, varied, fast and valuable data. The traditional information management systems do not respond to such massive and rapid inflows of information as is represented by the large amount of data generated today thanks to the technological developments and the creation of virtual ecosystems where there is an immense amount of interactions. The possibility of being able to convert that large amount of data into valuable information for the decision-making processes of the stakeholders is the great paradigm change that big data implies.Ítem Tendencias tecnológicas que transforman la medicina(Universidad EAFIT, 2020-08-08) Aguirre Eastman, Sebastián; ColaboradorÍtem Towards an improved asum-dm process methodology for cross-disciplinary multi-organization geographically-distributed big data & analytics projects(Universidad EAFIT, 2018) Angee Agudelo, Santiago; Tabares Betancur, Marta SilviaIn recent years, the big data & analytics projects developed in big enterprises or excellence centers have special conditions like being cross-disciplinary, having participants geographically distant one another, and the participation of several organizations. This has caused that traditional methodologies used to undertake data analytics, like CRISP-DM or other emerging methodologies, be not sufficient to perform an appropriate project management. This proposal uses Design Science Research Methodology (DSRM) to identify a problem, define the objectives for a solution, design, develop and show the usage of an ASUM-DM based big data & analytics process methodology for cross-disciplinary, multi-organization, geographically-distributed work teams. The results generated are a big data & analytics project management process methodology and a gap analysis applied on three enterprise-university use cases, showing how the proposed methodology can help address the big data characteristics of a project, and coordinate and integrate several multi-organization, geographically-distributed, cross-disciplinary work teams. This process methodology is expected to ease practitioners and researchers the implementation and management of big data & analytics projects with the participation of several cross-disciplinary work teams, and geographicallydistributed organizations.