The current requirements of the industry present challenges that must faced daily in the different productive sectors. The use of the cutting-edge technology and the efficient handling of large volumes of information allow the development of new computational tools that improve accuracy and optimize calculation’s times in pipe design. In this work the application is presented of the Piping Systems Analysis Program (PSAP), same that was developed as a graphical interface in the computer language MATLAB®; this computational application determines the size of the commercial pipe based on the pressure difference, elevation, water temperature and volume flow as critical design parameters. The algorithm of solution uses skills of Big Data for the precise handling of large volumes of information, getting accurate results at reduced times without compromising the reliability of pipe systems; this way optimizes the design process compared to traditional analytical methods.

The evolution of technology towards a new era of agile and dynamic workflows in the topic of cloud computing has resulted in professionals in Information Technology deepening in the study of tools or mechanisms that optimize the storage and data security; on the other hand, for companies that increasingly handle a larger volume of data to develop their activity, having these tools has become a key factor today. In this work is present the study of the Cinder component of the OpenStack platform, as a block storage tool that is associated with virtual machines or instances; is presented the deployment of a cloud platform of the IaaS model (Infrastructure as a Service) in a test environment, following the first four phases of the PDIOO methodology proposed by Cisco Systems; and the results that demonstrate the persistent storage of information through the use of said component are presented.

The purpose of the computer programs is to solve specific problems using a set of instructions composed of operations, logical decisions and repetitive cycles. The teaching-learning process uses in the early stages the Flow Diagrams that allow the student to graphically represent the sequence of a finite set of instructions but that is insufficient to learn to program due to the lack of experience and knowledge of the students in the area of programming, which consequently increases the rates of failure or attrition during the first semesters of their university education in the engineering career in computer systems, so it is necessary to develop additional resources for students to generate algorithmic thinking gradually. The methodology followed for the development of the project is based on the cascade life cycle with subprojects; Finally, with a group of 35 students, at the beginning 24 (68%) of them presented difficulties to analyze and program, using the didactic software as support in classes was reduced to 8 (22%).