Big Data Analytics in E-Governance and Other Aspects of Society

Big Data Analytics in E-Governance and Other Aspects of Society

Dishit Duggar, Sarang Mahesh Bang, B. K. Tripathy
Copyright: © 2023 |Pages: 13
DOI: 10.4018/978-1-7998-9220-5.ch007
OnDemand:
(Individual Chapters)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

Normally, big data refers to large and complex data sets that are derived from various sources and require new mechanisms for processing as existing mechanisms cannot handle such complex data (structured, semi-structured, and unstructured). Such type of data is growing rapidly in various sectors, and its interpretation and analysis is the need of today. Like other areas, e-governance and society also deal with big data. Big data analytics refers to the use of tools and techniques to process and analyse big data and plays a vital role in e-government projects. Using these tools, governments tend to modernize the public sector and create different policies to improve economy of a country. This article starts with a brief introduction to big data and its applications in e-governance and describes and analyses different available frameworks/tools highlighting their pros and cons. Also, frameworks being in different sectors of governance are presented along with various analytic techniques used. It ends with accounting challenges in using and managing big data analytics techniques.
Chapter Preview
Top

Introduction

The world is moving towards more digitized processes for everything, primarily due to the COVID-19 outbreak. This pandemic has compelled governments to invest in big data analytics technology to make the functioning of the public sector faster, scalable, and reliable. With technology speeding up, IT Services have been generating a large amount of big data, and it is harder to process using the traditional data processing technologies. With data growing at such a significant speed, developers need to analyze and make decisions based on big data for better results and recommendations (Tripathy and Deepthi, 2017), (Tripathy, 2017), (Divya and Tripathy, 2020). Having insight into this data will improve the system's overall efficiency (Srividya and Tripathy, 2021). Big Data's scalable nature can easily correlate data and enhance the overall results. All countries' central governments are pushing hard to get more and more citizens of their country online and further digitize the whole process. Governments are trying to make data readily available to people anywhere through digitization, thus saving their time and resources. Therefore data collected from different government schemes are getting added, and the size of this data is increasing exponentially day after day, there is a steep rise in data-driven projects across several countries. Therefore, Big data and E-governance is becoming a crucial aspect of a country's development.

Through E-governance, government facilities are provided to the citizens conveniently and transparently (Agnihotri and Sharma, 2015), (Salwan and Maan, 2020). E-Governance plays a significant role in uplifting the country's economy and making people use digitized apps and websites to reduce human error.

This paper focuses on the Role of Big Data analytics in E-Governance and Society, mainly describing and improving Government measures to manage such a large amount of data efficiently and securely.

Big Data

Big data refers to data sets that are large and complex derived from various sources. Usually, such data sets are too large to be processed using the database techniques and programming languages that make up the bulk of today's technologies. Big data can be structured, unstructured, or semi-structured. Most of the current methods only allow processing structured data and fail for the other two categories (Tripathy et al, 2017), (Seetha et al, 2017).

Big data can be collected from various sources such as information gathered from public apps and websites, public comments on social media sources, information on government schemes and policies, and many more. It is stored in complex, huge databases that can process this data, which is hard for the traditional databases.

Data stored is then processed and analyzed by Big data Analysts to derive insightful info patterns on how the data is being used and suggest changes in the existing system (Labrinidis and Hosagrahar, 2012), (Rajaraman, 2011). Big data has created many opportunities for all types of people. For example, increasing growth in customer data for a company makes them hire new sales representatives to meet the requirement and smooth functioning. This creates employment opportunities for skilled and semi-skilled youths. Small businesses see big data as an opportunity to expand their services in more regions and make their brand available to people.

Big data improves project operations, provides better services to the public by making data available to different government institutions, and helps make important decisions quickly and wisely. With the increase in data generation in various formats, i.e., text, audio, video, image, etc. It has not been easy to manage and analyze with the existing traditional tools, which only work for structured data (Chandarana et al, 2014).

Key Terms in this Chapter

Big Data Analytics: Big data analytics is defined as the use of advanced analytical tools to gain insight into a large volume of diverse data sets. These datasets contain structured, semi-structured, and unstructured data from various sources.

Batch Processing: Batch processing is the process of completing batches of jobs simultaneously in a sequential manner.

Message Passing Interface (MPI): Message passing interface is a process of exchanging messages between various computers across the distributed memory.

E-Governance: E-governance can be defined as the use of information and communication technology (ICTs) by governments to provide public services to people more efficiently and transparently.

Big Data: Big data is a collection of data that is larger in volume,has variety and cannot be processed by traditional tools.

Big Data Frameworks: Big data frameworks are tools that store and process massive datasets intending to benefit the organization from the big data.

Stream Processing: Stream processing is the process of evaluating or computing the data as it is received or created.

Complete Chapter List

Search this Book:
Reset