37 research outputs found
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
Storage Solutions for Big Data Systems: A Qualitative Study and Comparison
Big data systems development is full of challenges in view of the variety of
application areas and domains that this technology promises to serve.
Typically, fundamental design decisions involved in big data systems design
include choosing appropriate storage and computing infrastructures. In this age
of heterogeneous systems that integrate different technologies for optimized
solution to a specific real world problem, big data system are not an exception
to any such rule. As far as the storage aspect of any big data system is
concerned, the primary facet in this regard is a storage infrastructure and
NoSQL seems to be the right technology that fulfills its requirements. However,
every big data application has variable data characteristics and thus, the
corresponding data fits into a different data model. This paper presents
feature and use case analysis and comparison of the four main data models
namely document oriented, key value, graph and wide column. Moreover, a feature
analysis of 80 NoSQL solutions has been provided, elaborating on the criteria
and points that a developer must consider while making a possible choice.
Typically, big data storage needs to communicate with the execution engine and
other processing and visualization technologies to create a comprehensive
solution. This brings forth second facet of big data storage, big data file
formats, into picture. The second half of the research paper compares the
advantages, shortcomings and possible use cases of available big data file
formats for Hadoop, which is the foundation for most big data computing
technologies. Decentralized storage and blockchain are seen as the next
generation of big data storage and its challenges and future prospects have
also been discussed