These last years we have been witnessing a tremendous growth in the volume and availability of data. This fact results primarily from the emergence of a multitude of sources (e.g. computers, mobile devices, sensors or...These last years we have been witnessing a tremendous growth in the volume and availability of data. This fact results primarily from the emergence of a multitude of sources (e.g. computers, mobile devices, sensors or social networks) that are continuously producing either structured, semi-structured or unstructured data. Database Management Systems and Data Warehouses are no longer the only technologies used to store and analyze datasets, namely due to the volume and complex structure of nowadays data that degrade their performance and scalability. Big Data is one of the recent challenges, since it implies new requirements in terms of data storage, processing and visualization. Despite that, analyzing properly Big Data can constitute great advantages because it allows discovering patterns and correlations in datasets. Users can use this processed information to gain deeper insights and to get business advantages. Thus, data modeling and data analytics are evolved in a way that we are able to process huge amounts of data without compromising performance and availability, but instead by “relaxing” the usual ACID properties. This paper provides a broad view and discussion of the current state of this subject with a particular focus on data modeling and data analytics, describing and clarifying the main differences between the three main approaches in what concerns these aspects, namely: operational databases, decision support databases and Big Data technologies.展开更多
The great evolution of the mobile market during the last years caused some fragmentation of the mobile platforms namely through the existence of different programming languages and software development tools for each ...The great evolution of the mobile market during the last years caused some fragmentation of the mobile platforms namely through the existence of different programming languages and software development tools for each platform. This fact can be an obstacle and increases the development complexity and costs when we want to develop mobile applications for multiple platforms. The XIS-Mobile domain specific language (defined as a UML profile) and its MDD-based framework address this problem by proposing platform-independent models to describe mobile applications and from them automatically generate the application’s source code. Many issues arose during an iterative process of evaluation which originated changes and the evolution of XIS-Mobile. This paper presents the results of the evaluation of XIS-Mobile (both the language and the companion framework) obtained through the implementation of a case study and by conducting a user session, and discusses its benefits and challenges.展开更多
文摘These last years we have been witnessing a tremendous growth in the volume and availability of data. This fact results primarily from the emergence of a multitude of sources (e.g. computers, mobile devices, sensors or social networks) that are continuously producing either structured, semi-structured or unstructured data. Database Management Systems and Data Warehouses are no longer the only technologies used to store and analyze datasets, namely due to the volume and complex structure of nowadays data that degrade their performance and scalability. Big Data is one of the recent challenges, since it implies new requirements in terms of data storage, processing and visualization. Despite that, analyzing properly Big Data can constitute great advantages because it allows discovering patterns and correlations in datasets. Users can use this processed information to gain deeper insights and to get business advantages. Thus, data modeling and data analytics are evolved in a way that we are able to process huge amounts of data without compromising performance and availability, but instead by “relaxing” the usual ACID properties. This paper provides a broad view and discussion of the current state of this subject with a particular focus on data modeling and data analytics, describing and clarifying the main differences between the three main approaches in what concerns these aspects, namely: operational databases, decision support databases and Big Data technologies.
文摘The great evolution of the mobile market during the last years caused some fragmentation of the mobile platforms namely through the existence of different programming languages and software development tools for each platform. This fact can be an obstacle and increases the development complexity and costs when we want to develop mobile applications for multiple platforms. The XIS-Mobile domain specific language (defined as a UML profile) and its MDD-based framework address this problem by proposing platform-independent models to describe mobile applications and from them automatically generate the application’s source code. Many issues arose during an iterative process of evaluation which originated changes and the evolution of XIS-Mobile. This paper presents the results of the evaluation of XIS-Mobile (both the language and the companion framework) obtained through the implementation of a case study and by conducting a user session, and discusses its benefits and challenges.
