Recommendation of an integrated index for the quality of educational services using multivariate statistics

In this work, the analysis of the surveys was carried out through a factorial analysis, which facilitates the evaluation of the validity of the selected construct for the case under study, as well as evaluating the quality of the service for each factor, with a view to determining the level of quality of the educational service, for which it integrates elements of descriptive and multivariate statistics with the management of the quality of the educational service. They are used as fundamental statistical techniques, descriptive analysis, factor analysis and analysis of variance. As a final result, it was concluded that the students of five UNITEC careers evaluated the educational service they receive as very satisfactory (4 points), highlighting the tangible elements as the most weighted factor. A significant aspect is that there are no significant differences in the perceptions of students from different careers and different sections

Information consumption patterns from big data

Virtual social networks imply an important opportunity to generate friendlier communication bridges between students, teachers and other actors related to the educational field. In this sense, our study presents an approximation to the connection habits between university students in these networks, which in the future will allow to take advantage of these platforms to achieve a successful communication between actors. Thus, the characterization of uses, habits and consumption of virtual social networks becomes very relevant

Student performance assessment using clustering techniques

The application of informatics in the university system management allows managers to count with a great amount of data which, rationally treated, can offer significant help for the student programming monitoring. This research proposes the use of clustering techniques as a useful tool of management strategy to evaluate the progression of the students’ behavior by dividing the population into homogeneous groups according to their characteristics and skills. These applications can help both the teacher and the student to improve the quality of education. The selected method is the data grouping analysis by means of fuzzy logic using the Fuzzy C-means algorithm to achieve a standard indicator called Grade, through an expert system to enable segmentation.Universidad de la Costa, 2 Universidad Nacional Experimental Politécnica “Antonio José de Sucre”, Universidad Simón Bolívar, Corporación Universitaria Latinoamericana, Corporación Universitaria Minuto de Dios

Hybrid cloud computing architecture based on open source technology

The advance of technologies such as distributed computing, Internetand grid computing, have enabled Cloud Computing to become part of a new model of computing and business. Cloud Computing is transforming the traditional ways in which companies use and acquire Information Technology (IT) resources. After an initial boom in Public Cloud, companies begun to mount hybrid Clouds that offer the advantages of Cloud Computing in addition to the privacy of data they consider strategic. A hybrid Cloud solution allows the integration of both systems. Leading companies in cloud solutions have understood this evolution and begun to offer hybrid solutions. Moreover, many of these companies are taking the next step by offering solutions based on open source standards that allow a high degree of interoperability and portability

Data processing for direct marketing through Big Data

Traditional marketing performs promotion through various channels such as news in newspapers, radio, etc., but those promotions are aimed at all people, whether or not interested in the product or service being promoted. This method usually leads to high expenses and a low response rate by potential customers. That is why, nowadays, because there is a very competitive market, mass marketing is not safe, hence specialists are focusing efforts on direct marketing. This method studies the characteristics, needs and also selects a group of customers as a target for the promotion. Direct marketing uses predictive modeling from customer data, with the aim of selecting the most likely to respond to promotions. This research proposes a platform for the processing of data flows for target customer selection processes and the construction of required predictive response models

Effect on the demand and stock returns: cross-sectional of Big Data and time-series analysis

For reducing the degree of uncertainty caused by constant change in the environment, large, medium or small, private or public organizations must support their decisions in something more than experience or intuition; they must be supported by the development of accurate and reliable forecasts in order to meet the needs in the organization planning tasks. This case study presents a growing company dedicated to the storage of perishable products and incorporates time series forecasting techniques to estimate the volume of storage to foresee the requirements of additional facilities, personnel and materials needed for product mobility