Big Data Management in Education Sector: an Overview

The advancement in technological innovation has given rise to a new trend known as Big Data today. Given the soaring popularity of big data technology, organisations are profoundly attracted to and interested in it to transform their organisation by improving their businesses. Big data is enabling organisations to outpace their competitors and save cost. Similarly, the application of Big Data management in Universities is an essential aspect to institutions that have Big Data to manage; as the use of Big Data in the higher education sector is increasing day by day. Many studies have been carried out on big data and analytics with little interest in its management. Big Data management is a reality that represents a set of challenges involving Big Data modeling, storage, and retrieval, analysis, and visualization for several areas in organizations. This paper introduces and contributes to the conceptual and theoretical understanding of Big Data management within higher education as it outlines its relevance to higher education institutions. It describes the opportunities this growing research area brings to higher education as well as major challenges associated with it

Arithmetic Operations on Short Finite Sequences

In contrast to other proving systems Mizar Mathematical Library, considered as one of the largest formal mathematical libraries [4], is maintained as a single base of theorems, which allows the users to benefit from earlier formalized items [3], [2]. This eventually leads to a development of certain branches of articles using common notation and ideas. Such formalism for finite sequences has been developed since 1989 [1] and further developed despite of the controversy over indexing which excludes zero [6], also for some advanced and new mathematics [5].The article aims to add some new machinery for dealing with finite sequences, especially those of short length.Department of Carbohydrate Technology, University of Agriculture, Krakow, PolandGrzegorz Bancerek and Krzysztof Hryniewiecki. Segments of natural numbers and finite sequences. Formalized Mathematics,1(1):107–114, 1990.Grzegorz Bancerek, Czesław Byliński, Adam Grabowski, Artur Korniłowicz, Roman Matuszewski, Adam Naumowicz, Karol Pąk, and Josef Urban. Mizar: State-of-the-art and beyond. In Manfred Kerber, Jacques Carette, Cezary Kaliszyk, Florian Rabe, and Volker Sorge, editors, Intelligent Computer Mathematics, volume 9150 of Lecture Notes in Computer Science, pages 261–279. Springer International Publishing, 2015. ISBN 978-3-319-20614-1. doi:10.1007/978-3-319-20615-8_17.Grzegorz Bancerek, Czesław Byliński, Adam Grabowski, Artur Korniłowicz, Roman Matuszewski, Adam Naumowicz, and Karol Pąk. The role of the Mizar Mathematical Library for interactive proof development in Mizar. Journal of Automated Reasoning, 61(1):9–32, 2018. doi:10.1007/s10817-017-9440-6.Alexander Elizarov, Alexander Kirillovich, Evgeny Lipachev, and Olga Nevzorova. Digital ecosystem OntoMath: Mathematical knowledge analytics and management. In Leonid Kalinichenko, Sergei O. Kuznetsov, and Yannis Manolopoulos, editors, Data Analytics and Management in Data Intensive Domains, pages 33–46. Springer International Publishing, 2017.Adam Naumowicz and Artur Korniłowicz. A brief overview of Mizar. In International Conference on Theorem Proving in Higher Order Logics, pages 67–72. Springer, 2009. doi:10.1007/978-3-642-03359-9_5.Piotr Rudnicki and Andrzej Trybulec. On the integrity of a repository of formalized mathematics. Mathematical Knowledge Management, 2003. doi:10.1007/3-540-36469-2_13.26319920

Big Data Management in Education Sector: an Overview

The advancement in technological innovation has given rise to a new trend known as Big Data today. Given the soaring popularity of big data technology, organisations are profoundly attracted to and interested in it to transform their organisation by improving their businesses. Big data is enabling organisations to outpace their competitors and save cost. Similarly, the application of Big Data management in Universities is an essential aspect to institutions that have Big Data to manage; as the use of Big Data in the higher education sector is increasing day by day. Many studies have been carried out on big data and analytics with little interest in its management. Big Data management is a reality that represents a set of challenges involving Big Data modeling, storage, and retrieval, analysis, and visualization for several areas in organizations. This paper introduces and contributes to the conceptual and theoretical understanding of Big Data management within higher education as it outlines its relevance to higher education institutions. It describes the opportunities this growing research area brings to higher education as well as major challenges associated with it