PABED A Tool for Big Education Data Analysis

Cloud computing and big data have risen to become the most popular technologies of the modern world. Apparently, the reason behind their immense popularity is their wide range of applicability as far as the areas of interest are concerned. Education and research remain one of the most obvious and befitting application areas. This research paper introduces a big data analytics tool, PABED Project Analyzing Big Education Data, for the education sector that makes use of cloud-based technologies. This tool is implemented using Google BigQuery and R programming language and allows comparison of undergraduate enrollment data for different academic years. Although, there are many proposed applications of big data in education, there is a lack of tools that can actualize the concept into practice. PABED is an effort in this direction. The implementation and testing details of the project have been described in this paper. This tool validates the use of cloud computing and big data technologies in education and shall head start development of more sophisticated educational intelligence tools

Cassandra Data Modeling

To work with large amount of data consisting of 4 v�s velocity, variety, volume and veracity that is nothing but big data, so the need arises to find out the solution to work on such large scale data with high performance. NoSQL databases helps in this scenario. With Cassandra we can efficiently manage the large amount of structured data. It supports dynamic control over the data. In this paper, we present relational and Cassandra data modeling

Smart Grids Data Management: A Case for Cassandra

The objective of this paper is to present a SMACK based platform for microgrids data storage and management. The platform is being used in a real microgrid, with an infrastructure that monitors and controls 3 buildings within the GECAD - ISEP/IPP campus, while, at the same time, receives and manages data sources coming from different types of buildings from associated partners, to whom intelligent services are being provided. Microgrid data comes in different formats, different rates and with an increasing volume, as the microgrid itself covers more customers and areas. Based on the atual available computational resources, a Big Data platform based on the SMACK stack was implemented and is presented. The Cassandra component of the stack has evolved. AC version 2 is still supported until the version 4 release, and is often still used in production environments. However, a new stable version, version 3, introduces major optimizations in the storage that bring disk space savings. The main focus of this work is on the Data Storage and the formalization of the data mapping in Cassandra version 3, which is contextualized by means of a short example with data coming from the monitoring infrastructure of the microgrid.This work has received funding from EU Horizon 2020 R&D programme under Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO), EUREKA - ITEA2 Project FUSE-IT (nr.13023), Project GREEDI (ANI|P2020 17822), FEDER Funds through COMPETE program and National Funds FCT under the UID/EEA/00760/2013 and SFRH/BD/103089/2014.info:eu-repo/semantics/publishedVersio

Knowledge management system for big data in a smart electricity grid context

We have been witnessing a real explosion of information, due in large part to the development in Information and Knowledge Technologies (ICTs). As information is the raw material for the discovery of knowledge, there has been a rapid growth, both in the scientific community and in ICT itself, in the study of the Big Data phenomenon (Kaisler et al., 2014). The concept of Smart Grids (SG) has emerged as a way of rethinking how to produce and consume energy imposed by economic, political and ecological issues (Lund, 2014). To become a reality, SGs must be supported by intelligent and autonomous IT systems to make the right decisions in real time. Knowledge needed for real-time decision-making can only be achieved if SGs are equipped with systems capable of efficiently managing all the surrounding information. Thus, this paper proposes a system for the management of information in the context of SG to enable the monitoring, in real time, of the events that occur in the ecosystem and to predict following events.This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO) and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013.info:eu-repo/semantics/publishedVersio

Rancang Bangun Sistem Log Server Berbasis Syslog dan Cassandra untuk Monitoring Pengelolaan Jaringan di ITS

Semakin berkembangnya teknologi informasi menuntut semakin banyaknya penggunaan perangkat berupa komputer atau perangkat jaringan. Semakin banyak perangkat komputer yang digunakan akan membutuhkan biaya perawatan yang lebih besar, terutama ketika sistem administrator harus memeriksa pesan log semua perangkat komputernya. Syslog server adalah sebuah server yang menyimpan data syslog berbagai macam perangkat komputer dan jaringan secara terpusat. Syslog server harus memiliki ketersediaan tinggi untuk melayani penyimpanan syslog setiap perangkat komputer dan jaringan. Semakin banyak perangkat komputer dan jaringan yang harus dicatat lognya secara realtime menjadi tantangan tersendiri. Log tersebut juga harus dapat ditampilkan kembali dengan baik, agar sistem administrator dapat menganalisa log dengan mudah dan cepat. Muncul gagasan penggunaan Cassandra sebagai basis data penyimpanan syslog server. Cassandra sebagai penyimpanan utama syslog server didukung dengan nodeJS sebagai middleware yang digunakan untuk berinteraksi dengan cassandra diharapkan dapat menjadi sebuah lingkungan log server yang dapat menyimpan semua syslog secara terpusat. Hasil membuktikan penggunaan Cassandra sebagai penyimpanan data Syslog dapat membantu proses pengembangan sistem menjadi skala yang lebih besar dengan cepat dan tanpa adanya penghentian pada sistem yang sedang berjalan, Sehingga sistem dapat menangani lebih banyak perangkat

Mantenimiento de la Consistencia Lógica en Cassandra

A diferencia de las bases de datos relacionales, en bases de datos NoSQL como Cassandra es muy común que exista duplicidad de los datos en diferentes tablas. Esto es debido a que, normalmente, las tablas son diseñadas en base a las consultas y a la ausencia de relaciones entre ellas para primar el rendi miento en las consultas. Por tanto, si los datos no se actualizan convenientemente, se pueden producir inconsistencias en la información almacenada. Es relativa mente fácil introducir defectos que originan inconsistencia de datos en Cassan dra, sobre todo durante la evolución de un sistema en el que se crean nuevas tablas, y éstos son difíciles de detectar utilizando técnicas convencionales de pruebas dinámicas. El desarrollador es quien debe preocuparse de mantener esta consistencia incluyendo y actualizando los procedimientos adecuados. Este tra bajo propone un enfoque preventivo a estos problemas, estableciendo los proce sos necesarios para asegurar la calidad de los datos desde el punto de vista de su consistencia, facilitando así las tareas del desarrollador. Estos procesos incluyen: (1) un análisis estático considerando el modelo conceptual, las consultas y el mo delo lógico de la aplicación, para identificar qué elementos (tablas o columnas) de la base de datos se ven afectados por un cambio, y (2) la determinación y ejecución de las operaciones que aseguren la consistencia de la información.Ministerio de Economía y Competitividad TIN2016-76956-C3-1-R/-2-RPrincipado de Asturias GRUPIN14-00

Incorporando NOSQL en el currículo de Bases de Datos

En este trabajo se presentan aspectos curriculares y docentes relacionados con la incorporación de la enseñanza de las bases de datos denominadas NoSQL dentro del programa de la materia Base de Datos en la carrera de Ciencias de la Computación de la Facultad de Ciencias Exactas y Naturales de la Universidad de Buenos Aires. Si bien algunos de los temas vinculados a los modelos de bases de datos diferentes al modelo relacional se tratan en la materia desde hace tiempo, los mismos no tenían el peso específico necesario y sólo eran vistos en las clases teóricas. En este trabajo describimos un cambio cualitativo en la enseñanza de esos temas y su contextualización, tomando en cuenta la ubicuidad de las bases de datos, en el marco de la materia.Área: Educación en Tecnología.Red de Universidades con Carreras en Informática (RedUNCI