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La educación ha vivido una serie de transformaciones producto de la necesidad de dar respuesta a nuevos desafíos impuestos por la sociedad. En este contexto, el Aprendizaje Basado en Proyectos (ABPrj) surge como una metodología de enseñanza constructivista centrada en el alumnado. El objetivo de la investigación es presentar contribuciones relacionadas con la implementación del ABPrj como herramienta pedagógica de apoyo y mejora del proceso de enseñanza y aprendizaje de conceptos matemáticos en niveles de escolaridad primaria. Para lograrlo se realizará una revisión sistemática. El estudio es de tipo descriptivo con corte cuantitativo y diseño no experimental. Se concluye que el uso del ABPrj consiguió aumentar en la población objetivo la creatividad y el interés hacía las ciencias y las Matemáticas y facilitó la obtención de conocimientos y habilidades que pueden ser útiles ante situaciones de la vida real.

Transportation logistics aims to deliver products at the right time and place at the lowest possible cost. Within this activity are the problems of optimizing the routing of cargo vehicles that must travel a minimum cost route for the delivery of goods. The impact of the use of information technologies in the context of the supply chain can be measured basically in integration and in the benefits it brings. The objective of this research is to use computational simulation to evaluate restrictions of a messaging system and to show the shortest route found for three package delivery lines, optimizing the time and allocation of packages for each line. The project was developed under an empirical and exploratory methodology, where four phases followed. An algorithm was designed that used a voracious and stochastic approach, with an objective function that was evaluated in each of the n-simulations, to find the shortest route on the three delivery lines. To test the effectiveness of the algorithm, two test scenarios were carried out. In both scenarios, it was possible to show that the greater the number of simulations, the distance found was shorter, which was the objective of the investigation., A logística de transporte visa entregar os produtos na hora e no local certo com o menor custo possível. Dentro desta atividade estão os problemas de otimização do roteiro de veículos de carga que devem percorrer uma rota de custo mínimo para a entrega da mercadoria. O impacto do uso de tecnologias de informação no contexto da cadeia de suprimentos pode ser medido basicamente na integração e nos benefícios que ela traz. O objetivo desta pesquisa é utilizar simulação computacional para avaliar as restrições de um sistema de courier e obter a rota com menor distância encontrada para três linhas de entrega de pacotes, otimizando o tempo e a alocação de pacotes para cada linha. O projeto foi desenvolvido sob uma metodologia empírica e exploratória, onde se seguiram quatro fases. Foi desenhado um algoritmo que utilizou uma abordagem voraz e estocástica, com uma função objetivo que foi avaliada em cada uma das n-simulações, para encontrar o caminho de menor distância nas três linhas de entrega. Para verificar a eficácia do algoritmo, foram realizados dois cenários de teste. Em ambos os cenários, foi possível mostrar que, com um maior número de simulações, a distância encontrada foi menor, que foi o objetivo da investigação., La logística de transporte tiene como objetivo la entrega de productos en el momento y lugar correcto al menor costo posible. Dentro de esta actividad se encuentran los problemas de optimización del enrutamiento de vehículos de carga que deben recorrer una ruta de mínimo costo para la entrega de mercancías. El impacto que tiene el uso de tecnologías de la información en el contexto de cadena de suministro se puede medir básicamente en la integración y en los beneficios que aporta. La presente investigación tiene por objetivo utilizar la simulación computacional para evaluar restricciones de un sistema de mensajería y arrojar la ruta de menor distancia encontrada para tres líneas de entrega de paquetes, optimizando el tiempo y asignación de paquetes para cada línea. El proyecto se desarrolló bajo una metodología empírica y exploratoria, donde siguieron cuatro fases. Se diseñó un algoritmo que utilizo un enfoque voraz y estocástico, con una función objetivo que se evaluó en cada una de las n-simulaciones, para encontrar la ruta de menor distancia en las tres líneas de entrega. Para comprobar la efectividad del algoritmo se llevaron a cabo dos escenarios de prueba. En los dos escenarios, se logró evidenciar que, a mayor número de simulaciones, la distancia encontrada era menor, lo cual era el objetivo de la investigación.

La educación ha vivido una serie de transformaciones producto de la necesidad de dar respuesta a nuevos desafíos impuestos por la sociedad. En este contexto, el Aprendizaje Basado en Proyectos (ABPrj) surge como una metodología de enseñanza constructivista centrada en el alumnado. El objetivo de la investigación es presentar contribuciones relacionadas con la implementación del ABPrj como herramienta pedagógica de apoyo y mejora del proceso de enseñanza y aprendizaje de conceptos matemáticos en niveles de escolaridad primaria. Para lograrlo se realizará una revisión sistemática. El estudio es de tipo descriptivo con corte cuantitativo y diseño no experimental. Se concluye que el uso del ABPrj consiguió aumentar en la población objetivo la creatividad y el interés hacía las ciencias y las Matemáticas y facilitó la obtención de conocimientos y habilidades que pueden ser útiles ante situaciones de la vida real.

Education has experienced a series of transformations as a result of the need to respond to new challenges imposed by society. In this context, Project-Based Learning (ABPrj) emerges as a student-centered constructivist teaching methodology. The objective of the research is to present contributions related to the implementation of the ABPrj as a pedagogical tool to support and improve the teaching and learning process of mathematical concepts at primary school levels. To achieve this, a systematic review will be carried out. The study is descriptive with a quantitative cut and non-experimental design. It is concluded that the use of the ABPrj managed to increase creativity and interest in science and Mathematics in the target population, and facilitated the acquisition of knowledge and skills that can be useful in real life situations., La educación ha vivido una serie de transformaciones producto de la necesidad de dar respuesta a nuevos desafíos impuestos por la sociedad. En este contexto, el Aprendizaje Basado en Proyectos (ABPrj) surge como una metodología de enseñanza constructivista centrada en el alumnado. El objetivo de la investigación es presentar contribuciones relacionadas con la implementación del ABPrj como herramienta pedagógica de apoyo y mejora del proceso de enseñanza y aprendizaje de conceptos matemáticos en niveles de escolaridad primaria. Para lograrlo se realizará una revisión sistemática. El estudio es de tipo descriptivo con corte cuantitativo y diseño no experimental. Se concluye que el uso del ABPrj consiguió aumentar en la población objetivo la creatividad y el interés hacía las ciencias y las Matemáticas y facilitó la obtención de conocimientos y habilidades que pueden ser útiles ante situaciones de la vida real.

Before the Second World War, the Industrial Engineer's work focused on studies of plant distribution, quality control, production and inventories. Currently, these professionals are also required to carry out economic activities. The paper presents a business simulation game model that serves as a pedagogical tool for the teaching-learning process in the decision-making area, in the Marketing, Production and Finance disciplines. The research was carried out in four phases: data collection, reference frame construction, design construction, and testing. The theoretical and practical foundations were laid for future research, which improve the proposed model with the addition of Artificial Intelligence, Machine Learning and Deep Learning techniques, which optimize data processing and provide better support to the decision-making process., Antes de la segunda guerra mundial, el trabajo del Ingeniero Industrial se centraba en estudios de distribución en planta, control de calidad, producción e inventarios. En la actualidad, se requiere que estos profesionales también ejecuten actividades económicas. El artículo presenta un modelo de juego de simulación empresarial que sirva como herramienta pedagógica en el proceso de enseñanza-aprendizaje para el área de toma de decisiones, en las disciplinas de marketing, producción y finanzas. La investigación se desarrolló en cuatro fases: recolección de datos, construcción del marco de referencia, construcción del diseño y pruebas. Se sentaron las bases teóricas y prácticas para futuras investigaciones que mejoren el modelo propuesto con la adición de técnicas de Inteligencia Artificial, Machine Learning y Deep Learning, que optimicen el procesamiento de datos y brinden un mejor apoyo al proceso de toma de decisiones.

Introducción: El problema de la ruta más corta o ruta de mínimo costo, ha sido uno de los temas más estudiados por áreas del conocimiento como la Investigación de Operaciones, la Ciencias de la Computación y la Decisión, las Telecomunicaciones, la Distribución en Planta, la Planeación de Proyectos, entre otras, buscando, por ejemplo; optimizar y reducir los costos que representan la distribución de mercancías, obtener la mínima cantidad de tiempo necesaria para finalizar un proyecto, o calcular la ruta más corta posible entre ordenadores conectados a una red. Objetivo: Estudiar el comportamiento de tres algoritmos voraces que permiten calcular la ruta de mínimo costo entre dos puntos (estado inicial y estado objetivo) en un grafo ponderado y con heurísticas. Metodología: Se implementó una aplicación en Java, y se ajustaron los algoritmos Greedy, A* y Dijkstra al problema en cuestión. Posteriormente se diseñaron dos casos de instancia, una negativa y otra positiva. Resultados: En los resultados de instancia negativa se modificó la heurística del nodo para permitir al algoritmo seleccionado escapar de óptimos locales y así, obtener un resultado completo, es decir llegar al estado objetivo, que, en algunas ocasiones, no necesariamente será el resultado más óptimo. Conclusiones: Mediante la comparación entre los tres algoritmos se pudo determinar que el algoritmo de Dijkstra siempre arroja resultados completos y óptimos. Por su parte, Greedy y A*, necesitan de heurísticas para llegar a un resultado completo, pero no óptimo., Introduction: The problem of the shortest route or minimum cost route, has been one of the topics most studied by areas of knowledge such as Operations Research, Computer Science and Decision, Telecommunications, Plant Distribution, Planning of Projects, among others, searching, for example; optimize and reduce the costs that represent the distribution of goods, obtain the minimum amount of time necessary to complete a project, or calculate the shortest possible route between computers connected to a network. Objective: We will study the behavior of three voracious algorithms that allow us to calculate the minimum cost route between two points (initial state and objective state) in a weighted graph and with heuristics. Method: Was implemented in Java, and the Greedy, A* and Dijkstra algorithms were adjusted to the problem in question. Subsequently, two instance cases were designed, one negative and one positive. Results: In the negative instance results the heuristic of the node was modified to allow the selected algorithm to escape from local optima and thus obtain a complete result, that is to say reach the objective state, which, in some cases, will not necessarily be the most optimal result. Conclusions: By comparing the three algorithms, it was determined that the Dijkstra algorithm always yields complete and optimal results. For its part, Greedy and A *, need heuristics to reach a complete result, but not optimal.

This article presents the implementation of a priority queue with simulated parameterized components on the scenario of a banking institution in which four main elements were used: 1) the dispenser, 2) the cashier(s), 3) the server that receives and assigns the priority of the turns, and 4) a screen that displays the order of the turns. In any banking institution, there is always a large number of users that require attention, so they implement special turns to give priority to customers, improving the quality of service. One of the important elements within the cycle of service provision is related to the waiting lines, commonly called queues. Basically one queue is managed with the First-In, First-Out discipline. In this aspect, disciplines such as queuing theory help to understand the behavior of queues by examining all the components of the waiting lists. One of the most used disciplines for the management of a queue, is the enqueue with priority. In a priority queue, the element with the highest priority is removed before any other elements. The research was carried out using mainly a quantitative approach. The main goal of this type of research is the formulation and demonstration of theories and seeks that the studies carried out can be replicated. The algorithm implemented highly parameterizable allowed the correct simulation of a priority queue that can be taken as a basis for a subsequent application in any type of organization., Este artículo presenta la implementación de una cola de prioridad con componentes parametrizables simulada sobre el escenario de una institución bancaria en la cual se utilizaron cuatro elementos principales: 1) el dispensador de turnos, 2) el cajero(s) encargado de la atención, 3) el servidor que recibe y asigna la prioridad de los turnos, y 4) una pantalla que visualiza el orden de los turnos. En cualquier institución bancaria, siempre hay un gran número de usuarios que requieren atención, por lo que implementan turnos especiales para dar prioridad a los clientes, mejorando la calidad del servicio. Uno de los elementos importantes dentro del ciclo de provisión de servicios está relacionado con las líneas de espera, comúnmente llamadas colas. Básicamente una cola se gestiona con la disciplina First-In, First-Out. En este aspecto, disciplinas como la teoría de colas ayudan a comprender el comportamiento de las colas al examinar todos los componentes de las listas de espera. Una de las disciplinas más utilizadas para la gestión de una cola, es el encolado con prioridad. En una cola de prioridad, el elemento con la prioridad más alta se elimina antes que cualquier otro elemento. La investigación se realizó utilizando principalmente un enfoque cuantitativo. El objetivo principal de este tipo de investigación es la formulación y demostración de teorías y busca que los estudios realizados puedan replicarse. El algoritmo implementado altamente parametrizable permitió la correcta simulación de una cola de prioridad que puede tomarse como base para una aplicación posterior en cualquier tipo de organización.

We are currently in an era of information explosion that affects our life in one way or another. Because of this, the transformation of huge databases into knowledge has become one of the tasks of greatest interest to society in general. Big Data was born as an instrument for knowledge due to the inability of current computer systems to store and process large volumes of data. The knowledge society arises from the use of technologies such as Big Data. The purpose of this article is to analyze the influence of Big Data on the knowledge society through a review of the state of the art supported by research articles and books published in the last 15 years, which allow us to put these two terms into context, understand their relationship and highlight the influence of Big Data as a generator of knowledge for today's society. The concept of Big Data, and its main applications to society will be defined. The concept of the Information Society is addressed and the main challenges it has are established. The relationship between both concepts is determined. And finally the conclusions are established. In order to reduce the digital divide, it is imperative to make profound long-term changes in educational models and public policies on investment, technology and employment that allow the inclusion of all social classes. In this sense, knowledge societies with the help of Big Data are called to be integrative elements and transform the way they are taught and learned, the way they are investigated, new social and economic scenarios are simulated, the brand decisions in Companies and share knowledge.

We are currently in an era of information explosion that affects our life in one way or another. Because of this, the transformation of huge databases into knowledge has become one of the tasks of greatest interest to society in general. Big Data was born as an instrument for knowledge due to the inability of current computer systems to store and process large volumes of data. The knowledge society arises from the use of technologies such as Big Data. The purpose of this article is to analyze the influence of Big Data on the knowledge society through a review of the state of the art supported by research articles and books published in the last 15 years, which allow us to put these two terms into context, understand their relationship and highlight the influence of Big Data as a generator of knowledge for today's society. The concept of Big Data, and its main applications to society will be defined. The concept of the Information Society is addressed and the main challenges it has are established. The relationship between both concepts is determined. And finally the conclusions are established. In order to reduce the digital divide, it is imperative to make profound long-term changes in educational models and public policies on investment, technology and employment that allow the inclusion of all social classes. In this sense, knowledge societies with the help of Big Data are called to be integrative elements and transform the way they are taught and learned, the way they are investigated, new social and economic scenarios are simulated, the brand decisions in Companies and share knowledge.

We are currently in an era of information explosion that affects our life in one way or another. Because of this, the transformation of huge databases into knowledge has become one of the tasks of greatest interest to society in general. Big Data was born as an instrument for knowledge due to the inability of current computer systems to store and process large volumes of data. The knowledge society arises from the use of technologies such as Big Data. The purpose of this article is to analyze the influence of Big Data on the knowledge society through a review of the state of the art supported by research articles and books published in the last 15 years, which allow us to put these two terms into context, understand their relationship and highlight the influence of Big Data as a generator of knowledge for today's society. The concept of Big Data, and its main applications to society will be defined. The concept of the Information Society is addressed and the main challenges it has are established. The relationship between both concepts is determined. And finally the conclusions are established. In order to reduce the digital divide, it is imperative to make profound long-term changes in educational models and public policies on investment, technology and employment that allow the inclusion of all social classes. In this sense, knowledge societies with the help of Big Data are called to be integrative elements and transform the way they are taught and learned, the way they are investigated, new social and economic scenarios are simulated, the brand decisions in Companies and share knowledge.

We are currently in an era of information explosion that affects our life in one way or another. Because of this, the transformation of huge databases into knowledge has become one of the tasks of greatest interest to society in general. Big Data was born as an instrument for knowledge due to the inability of current computer systems to store and process large volumes of data. The knowledge society arises from the use of technologies such as Big Data. The purpose of this article is to analyze the influence of Big Data on the knowledge society through a review of the state of the art supported by research articles and books published in the last 15 years, which allow us to put these two terms into context, understand their relationship and highlight the influence of Big Data as a generator of knowledge for today's society. The concept of Big Data, and its main applications to society will be defined. The concept of the Information Society is addressed and the main challenges it has are established. The relationship between both concepts is determined. And finally the conclusions are established. In order to reduce the digital divide, it is imperative to make profound long-term changes in educational models and public policies on investment, technology and employment that allow the inclusion of all social classes. In this sense, knowledge societies with the help of Big Data are called to be integrative elements and transform the way they are taught and learned, the way they are investigated, new social and economic scenarios are simulated, the brand decisions in Companies and share knowledge.

We are currently in an era of information explosion that affects our life in one way or another. Because of this, the transformation of huge databases into knowledge has become one of the tasks of greatest interest to society in general. Big Data was born as an instrument for knowledge due to the inability of current computer systems to store and process large volumes of data. The knowledge society arises from the use of technologies such as Big Data. The purpose of this article is to analyze the influence of Big Data on the knowledge society through a review of the state of the art supported by research articles and books published in the last 15 years, which allow us to put these two terms into context, understand their relationship and highlight the influence of Big Data as a generator of knowledge for today's society. The concept of Big Data, and its main applications to society will be defined. The concept of the Information Society is addressed and the main challenges it has are established. The relationship between both concepts is determined. And finally the conclusions are established. In order to reduce the digital divide, it is imperative to make profound long-term changes in educational models and public policies on investment, technology and employment that allow the inclusion of all social classes. In this sense, knowledge societies with the help of Big Data are called to be integrative elements and transform the way they are taught and learned, the way they are investigated, new social and economic scenarios are simulated, the brand decisions in Companies and share knowledge.

This article presents the implementation of a priority queue with simulated parameterized components on the scenario of a banking institution in which four main elements were used: 1) the dispenser, 2) the cashier(s), 3) the server that receives and assigns the priority of the turns, and 4) a screen that displays the order of the turns. In any banking institution, there is always a large number of users that require attention, so they implement special turns to give priority to customers, improving the quality of service. One of the important elements within the cycle of service provision is related to the waiting lines, commonly called queues. Basically one queue is managed with the First-In, First-Out discipline. In this aspect, disciplines such as queuing theory help to understand the behavior of queues by examining all the components of the waiting lists. One of the most used disciplines for the management of a queue, is the enqueue with priority. In a priority queue, the element with the highest priority is removed before any other elements. The research was carried out using mainly a quantitative approach. The main goal of this type of research is the formulation and demonstration of theories and seeks that the studies carried out can be replicated. The algorithm implemented highly parameterizable allowed the correct simulation of a priority queue that can be taken as a basis for a subsequent application in any type of organization., Este artículo presenta la implementación de una cola de prioridad con componentes parametrizables simulada sobre el escenario de una institución bancaria en la cual se utilizaron cuatro elementos principales: 1) el dispensador de turnos, 2) el cajero(s) encargado de la atención, 3) el servidor que recibe y asigna la prioridad de los turnos, y 4) una pantalla que visualiza el orden de los turnos. En cualquier institución bancaria, siempre hay un gran número de usuarios que requieren atención, por lo que implementan turnos especiales para dar prioridad a los clientes, mejorando la calidad del servicio. Uno de los elementos importantes dentro del ciclo de provisión de servicios está relacionado con las líneas de espera, comúnmente llamadas colas. Básicamente una cola se gestiona con la disciplina First-In, First-Out. En este aspecto, disciplinas como la teoría de colas ayudan a comprender el comportamiento de las colas al examinar todos los componentes de las listas de espera. Una de las disciplinas más utilizadas para la gestión de una cola, es el encolado con prioridad. En una cola de prioridad, el elemento con la prioridad más alta se elimina antes que cualquier otro elemento. La investigación se realizó utilizando principalmente un enfoque cuantitativo. El objetivo principal de este tipo de investigación es la formulación y demostración de teorías y busca que los estudios realizados puedan replicarse. El algoritmo implementado altamente parametrizable permitió la correcta simulación de una cola de prioridad que puede tomarse como base para una aplicación posterior en cualquier tipo de organización.

We are currently in an era of information explosion that affects our life in one way or another. Because of this, the transformation of huge databases into knowledge has become one of the tasks of greatest interest to society in general. Big Data was born as an instrument for knowledge due to the inability of current computer systems to store and process large volumes of data. The knowledge society arises from the use of technologies such as Big Data. The purpose of this article is to analyze the influence of Big Data on the knowledge society through a review of the state of the art supported by research articles and books published in the last 15 years, which allow us to put these two terms into context, understand their relationship and highlight the influence of Big Data as a generator of knowledge for today's society. The concept of Big Data, and its main applications to society will be defined. The concept of the Information Society is addressed and the main challenges it has are established. The relationship between both concepts is determined. And finally the conclusions are established. In order to reduce the digital divide, it is imperative to make profound long-term changes in educational models and public policies on investment, technology and employment that allow the inclusion of all social classes. In this sense, knowledge societies with the help of Big Data are called to be integrative elements and transform the way they are taught and learned, the way they are investigated, new social and economic scenarios are simulated, the brand decisions in Companies and share knowledge.

We are currently in an era of information explosion that affects our life in one way or another. Because of this, the transformation of huge databases into knowledge has become one of the tasks of greatest interest to society in general. Big Data was born as an instrument for knowledge due to the inability of current computer systems to store and process large volumes of data. The knowledge society arises from the use of technologies such as Big Data. The purpose of this article is to analyze the influence of Big Data on the knowledge society through a review of the state of the art supported by research articles and books published in the last 15 years, which allow us to put these two terms into context, understand their relationship and highlight the influence of Big Data as a generator of knowledge for today's society. The concept of Big Data, and its main applications to society will be defined. The concept of the Information Society is addressed and the main challenges it has are established. The relationship between both concepts is determined. And finally the conclusions are established. In order to reduce the digital divide, it is imperative to make profound long-term changes in educational models and public policies on investment, technology and employment that allow the inclusion of all social classes. In this sense, knowledge societies with the help of Big Data are called to be integrative elements and transform the way they are taught and learned, the way they are investigated, new social and economic scenarios are simulated, the brand decisions in Companies and share knowledge.

We are currently in an era of information explosion that affects our life in one way or another. Because of this, the transformation of huge databases into knowledge has become one of the tasks of greatest interest to society in general. Big Data was born as an instrument for knowledge due to the inability of current computer systems to store and process large volumes of data. The knowledge society arises from the use of technologies such as Big Data. The purpose of this article is to analyze the influence of Big Data on the knowledge society through a review of the state of the art supported by research articles and books published in the last 15 years, which allow us to put these two terms into context, understand their relationship and highlight the influence of Big Data as a generator of knowledge for today's society. The concept of Big Data, and its main applications to society will be defined. The concept of the Information Society is addressed and the main challenges it has are established. The relationship between both concepts is determined. And finally the conclusions are established. In order to reduce the digital divide, it is imperative to make profound long-term changes in educational models and public policies on investment, technology and employment that allow the inclusion of all social classes. In this sense, knowledge societies with the help of Big Data are called to be integrative elements and transform the way they are taught and learned, the way they are investigated, new social and economic scenarios are simulated, the brand decisions in Companies and share knowledge.

We are currently in an era of information explosion that affects our life in one way or another. Because of this, the transformation of huge databases into knowledge has become one of the tasks of greatest interest to society in general. Big Data was born as an instrument for knowledge due to the inability of current computer systems to store and process large volumes of data. The knowledge society arises from the use of technologies such as Big Data. The purpose of this article is to analyze the influence of Big Data on the knowledge society through a review of the state of the art supported by research articles and books published in the last 15 years, which allow us to put these two terms into context, understand their relationship and highlight the influence of Big Data as a generator of knowledge for today's society. The concept of Big Data, and its main applications to society will be defined. The concept of the Information Society is addressed and the main challenges it has are established. The relationship between both concepts is determined. And finally the conclusions are established. In order to reduce the digital divide, it is imperative to make profound long-term changes in educational models and public policies on investment, technology and employment that allow the inclusion of all social classes. In this sense, knowledge societies with the help of Big Data are called to be integrative elements and transform the way they are taught and learned, the way they are investigated, new social and economic scenarios are simulated, the brand decisions in Companies and share knowledge.

We are currently in an era of information explosion that affects our life in one way or another. Because of this, the transformation of huge databases into knowledge has become one of the tasks of greatest interest to society in general. Big Data was born as an instrument for knowledge due to the inability of current computer systems to store and process large volumes of data. The knowledge society arises from the use of technologies such as Big Data. The purpose of this article is to analyze the influence of Big Data on the knowledge society through a review of the state of the art supported by research articles and books published in the last 15 years, which allow us to put these two terms into context, understand their relationship and highlight the influence of Big Data as a generator of knowledge for today's society. The concept of Big Data, and its main applications to society will be defined. The concept of the Information Society is addressed and the main challenges it has are established. The relationship between both concepts is determined. And finally the conclusions are established. In order to reduce the digital divide, it is imperative to make profound long-term changes in educational models and public policies on investment, technology and employment that allow the inclusion of all social classes. In this sense, knowledge societies with the help of Big Data are called to be integrative elements and transform the way they are taught and learned, the way they are investigated, new social and economic scenarios are simulated, the brand decisions in Companies and share knowledge.

We are currently in an era of information explosion that affects our life in one way or another. Because of this, the transformation of huge databases into knowledge has become one of the tasks of greatest interest to society in general. Big Data was born as an instrument for knowledge due to the inability of current computer systems to store and process large volumes of data. The knowledge society arises from the use of technologies such as Big Data. The purpose of this article is to analyze the influence of Big Data on the knowledge society through a review of the state of the art supported by research articles and books published in the last 15 years, which allow us to put these two terms into context, understand their relationship and highlight the influence of Big Data as a generator of knowledge for today's society. The concept of Big Data, and its main applications to society will be defined. The concept of the Information Society is addressed and the main challenges it has are established. The relationship between both concepts is determined. And finally the conclusions are established. In order to reduce the digital divide, it is imperative to make profound long-term changes in educational models and public policies on investment, technology and employment that allow the inclusion of all social classes. In this sense, knowledge societies with the help of Big Data are called to be integrative elements and transform the way they are taught and learned, the way they are investigated, new social and economic scenarios are simulated, the brand decisions in Companies and share knowledge.

We are currently in an era of information explosion that affects our life in one way or another. Because of this, the transformation of huge databases into knowledge has become one of the tasks of greatest interest to society in general. Big Data was born as an instrument for knowledge due to the inability of current computer systems to store and process large volumes of data. The knowledge society arises from the use of technologies such as Big Data. The purpose of this article is to analyze the influence of Big Data on the knowledge society through a review of the state of the art supported by research articles and books published in the last 15 years, which allow us to put these two terms into context, understand their relationship and highlight the influence of Big Data as a generator of knowledge for today's society. The concept of Big Data, and its main applications to society will be defined. The concept of the Information Society is addressed and the main challenges it has are established. The relationship between both concepts is determined. And finally the conclusions are established. In order to reduce the digital divide, it is imperative to make profound long-term changes in educational models and public policies on investment, technology and employment that allow the inclusion of all social classes. In this sense, knowledge societies with the help of Big Data are called to be integrative elements and transform the way they are taught and learned, the way they are investigated, new social and economic scenarios are simulated, the brand decisions in Companies and share knowledge.