A Systematic Literature Map on Big Data

The paradigm of Big Data has been established as a solid field of studies in many areas such as healthcare, science, transport, education, government services, among others. Despite widely discussed, there is no agreed definition about the paradigm although there are many concepts proposed by the academy and industry. This work aims to provide an analytical view of the studies conducted and published regarding the Big Data paradigm. The approach used is the systematic map of the literature, combining bibliometric analysis and content analysis to depict the panorama of research works, identifying patterns, trends, and gaps. The results indicate that there is still a long way to go, both in research and in concepts, such as building and defining adequate infrastructures and standards, to meet future challenges and for the paradigm to become effective and bring the expected benefits.

Chatbot Based Solution for Supporting Software Incident Management Process

A set of steps for implementing a chatbot, to support decision-making activities in the software incident management process is proposed and discussed in this article. Each step is presented independently of the platform used for the construction of chatbots and are detailed with their respective activities. The proposed steps can be carried out in a continuous and adaptable way, favoring the constant training of a chatbot and allowing the increasingly cohesive interpretatin of the intentions of the specialists who work in the Software Incident Management Process. The software incident resolution process accordingly to the ITIL framework, is considered for the experiment. The results of the work present the steps for the chatbot construction, the solution based on DialogFlow platform and some conclusions based on the experiment.

EXSeQETIC: Expert System to Support the Implementation of eQETIC Model

The digital educational solutions are increasingly used demanding high quality functionalities. In this sense, standards and models are made available by governments, associations, and researchers being most used in quality control and assessment sessions. The eQETIC model was built according to the approach of continuous process improvement favoring the quality management for development and maintenance of digital educational solutions. This article presents two expert systems to support the implementation of eQETIC model and demonstrates that such systems are able to support users during the model implementation. Developed according to two types of shells (SINTA/UFC and e2gLite/eXpertise2go), the systems were used by a professional who develops these type of solutions and showed positive results regarding the support offered by them in implementing the rules proposed by eQETIC model.

Characterizing Big Data Management

Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any kind of organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management can be supported by these three dimensions: technology, people and processes. Hence, this article discusses these dimensions: the technological dimension that is related to storage, analytics and visualization of big data; the human aspects of big data; and, in addition, the process management dimension that involves in a technological and business approach the aspects of big data management.