Integrating E-Governance with Big Data Analytics using Apache Spark

Abstract

The constant innovations and rapid developments in the IT industry have revolutionized the thinking and mindset of the people throughout the world. Government departments have also been computerized to provide transparent, efficient and responsible government through e-governance. The government have been providing access to various websites or portal for filing complaints, uploading or downloading forms, pictures, data or PDFs to avail the government services. Enlightened citizens are frequently using the portal to access government services. Thus, the size and volume of data that need to be managed by government departments have been increasing drastically under e-governance. The traditional database management system is not designed to deal with such mix type of data. Moreover, the speed at which the e-governance generated data need to be processed is another big challenge being faced by traditional database system. All the abovesaid concerns can be solved by using the emerging technology - Big Data Analytics techniques. Big data analytic techniques can make the government more efficient and transparent by processing structured, unstructured or mixed types data at a great speed. In this paper, we shall understand the scenario for the need or the emergence of big data analytics in egovernance and knowhow of Apache Spark. This paper proposes a practical approach to integrate big data analytics with egovernance using Apache Spark. This paper also reflects how major issues of traditional database management system (mixed type datasets, speed and accuracy) can be resolved through the integration of big data analytics and e-governance.

Big Data Analytics and Firm Performance: An Empirical Investigation of Direct and Mediating Effects

“…In addition, the developments of information and communication technology (ICT), the emergence of E-commerce, Electronic Data Interchange (EDI), cloud computing, and the Internet of Things (IoT) have introduced a large volume of data (Tan et al 2017;Ferraris et al 2019;Li and Liu 2020). Big data refers to the complex amount of data that cannot be stored, processed, and analyzed by a database system or traditional data processing application (Salwan and Maan 2020;Casarotto et al 2021). Due to the big data, the semi-structured and unstructured data have been increased and the traditional data analytics tools cannot analyze those types of data (Lee at el.…”

“…Traditional data analytics like UNIX are not efficient for storing and analyzing a large amount of data by using a single machine (Salwan and Maan 2020).…”

“…Apache Spark is another tool for analyzing big data, which provides faster processing at a lower time than Hadoop (Salwan and Maan 2020)…”