Factors Influencing Big Data Analytics in Public Sector: A Quick Overview (original) (raw)
Journal of Data and Information Quality, 2021
The public sector, private firms, business community, and civil society are generating data that are high in volume, veracity, and velocity and come from a diversity of sources. This type of data is today known as big data. Public administrations pursue big data as “new oil” and implement data-centric policies to collect, generate, process, share, exploit, and protect data for promoting good governance, transparency, innovative digital services, and citizens’ engagement in public policy. All of the above constitute the Government Big Data Ecosystem (GBDE). Despite the great interest in this ecosystem, there is a lack of clear definitions, the various important types of government data remain vague, the different actors and their roles are not well defined, while the impact in key public administration sectors is not yet deeply understood and assessed. Such research and literature gaps impose a crucial obstacle for a better understanding of the prospects and nascent issues in exploit...
Business intelligence addressing service quality for big data analytics in public sector
Indonesian Journal of Electrical Engineering and Computer Science, 2019
With the inauguration of Big Data Analytics initiative nationally, many nations have participated and paved way for BDA ecosystem. The initiative is a catalyst to further encourage economic growth in Public Sectors. Some of the common key deliverables identified are increasing productivity involving information communications technology, cost savings, shared benefits, and encourage innovation. The objectives can be further elaborated by driving big data analytics demands in various public sectors agency, adopting big data analytics framework supporting the building of big data industry. This has encouraged talents and startup companies inspiring their capabilities by developing various technology platform, collaborate and innovate amongst public and private sectors, and further strengthen data governance by creating policy and procedures. With the establishment of big data analytics framework, performance measurement can be enforced effortlessly using the principles of business intelligence maturity model and the technological stack comes with it. Various data sources can be used to benchmark service quality using advanced analytics and data science techniques.
Big Data and Algorithms in the Public Sector and Their Impact on the Transparency of Decision-Making
Central and Eastern European eDem and eGov Days, 2018
Big Data is clearly one of the most used buzzwords nowadays, but it really seems that the phenomenon of Big Data will have a huge effect on many different fields, and may be regarded as the new wave of the information revolution started in the 60s of the last century. The potential of exploiting Big Data promises significant benefits (and also new challenges) both in the private and the public sector-this essay will focus on this latter. After a short introduction about Big Data, this paper will first sum up the potential use of Big Data analytics in the public sector. Then I will focus on a specific issue within this scope, namely, how the use of Big Data and algorithm-based decision-making may affect transparency and access to these data. I will focus on the question why the transparency of the algorithms is raised at all, and what the current legal framework for the potential accessibility to them is.
Big-data applications in the government sector
Communications of the ACM, 2014
Big data, a general term for the massive amount of digital data being collected from all sorts of sources, is too large, raw, or unstructured for analysis through conventional relational database techniques. Almost 90% of the world's data today was generated during the past two years, with 2.5 quintillion bytes of data added each day. 7 Moreover, approximately 90% of it is unstructured. Still, the overwhelming amount of big data from the Web and the cloud offers new opportunities for discovery, value creation, and rich business intelligence for decision support in any organization. Big data also means new challenges involving complexity, security, and risks to privacy, as well as a need for new technology and human skills.
Big Data in the Public Sector : Systematic Literature Review and Bibliometric Analysis
Jurnal Ilmiah Mandala Education
This research aims to study and analyze systematically and in depth how Big Data is implemented in the public sector. The research method uses a systematic literature review and bibliometric analysis. The stages in the literature review using the PRISMA technique are identification, screening, equity and inclusion. Bibliometric Analysis is used to see research trends and their relationship with other studies. Search articles using a database of internationally reputed journals such as elsevier, springer, francis and taylor and wiley published from 2015 to 2021. Processing of bibliometric analysis using the Vos Viewer device. Based on the Publish and Perish search, 473 articles related to the research theme were generated. The results show that the application of big data in the public sector can improve the performance of government employees, increase efficiency and optimization of the bureaucracy and big data in the smallholder agricultural sector can answer the challenges of food...
Big data analytics (BDA) represents a new technological paradigm with its ability to extract valuable knowledge from high amounts of data. Exploring the effect of data quality dimensions (DQD) and big data traits (BDT) on BDA application is a relatively new research trend that has not been featured in the existing literature. Thus, this study was conducted to build a new model by integrating the DQD and BDT to examine the BDA application in the context of the Malaysian public sector. This study proposes that the DQD should include intrinsic, contextual, representational, and accessibility dimensions, while variety, validity, and veracity should be considered as the main characteristics of BDT. For this purpose, this study employed theory analysis on ongoing research related to DQD and BDT, along with the development of the BDA application model. The proposed model would create new research fields related to DQD and BDT in the BDA domain. Finally, in line with the Public Sector Big Data (DRSA) platform initiated by the Malaysian Administrative Modernisation and Management Planning Unit (MAMPU), the new model is expected to provide a benchmark for the development and application of BDA for the Malaysian public sector.
THE CRITICAL SUCCESS FACTORS FOR BIG DATA ADOPTION IN GOVERNMENT
IAEME, 2019
Over the past decade, governments around the world have been trying to take advantage of Big Data technology to improve public services with citizens. The adoption of Big Data has increased in most countries, but at the same time, the rate of successful adoption and management varies from one country to another. A systematic review of the literature (SLR) was carried out to identify the critical success factors (CSF) for the adoption of big data in the government. It includes the critical success factor of the adoption of Big Data in the government in the last 10 years. It presents the general trends that examine 183 journals and numerous literary works related to government operations, the provision of public services, citizen participation, decision making and policies, and governance reform. We selected 90 journals and found 11 classification factors that refer to the successions of a Big Data adoption in the government.
Big Data for Digital Government
Politics and Social Activism: Concepts, Methodologies, Tools, and Applications
Big data" is one of the emerging and critical issues facing government in the digital age. This study first delineates the defining features of big data (volume, velocity, and variety) and proposes a big data typology that is suitable for the public sector. This study then examines the opportunities of big data in generating business analytics to promote better utilization of information and communication technology (ICT) resources and improved personalization of e-government services. Moreover, it discusses the big data management challenges in building appropriate governance structure, integrating diverse data sources, managing digital privacy and security risks, and acquiring big data talent and tools. An effective big data management strategy to address these challenges should develop a stakeholder-focused and performance-oriented governance structure and build capacity for data management and business analytics as well as leverage and prioritize big data assets for performance. In addition, this study illustrates the opportunities, challenges, and strategy for big service data in government with the E-housekeeper program in Taiwan. This brief case study offers insight into the implementation of big data for improving government information and services. This article concludes with the main findings and topics of future research in big data for public administration.
2017
Evolution and growth of data exclusively in Government sector should be an added advantage for the Government to increase the service delivery to the public. Big Data Analytics (BDA) is one of the most advanced technologies to analyse data owned by the Government to explore other fields, or new opportunities that can bring benefits to the Government. Although BDA concept has been implemented by many parties, there exists a number of misconceptions related to the concept from the aspect of understanding and implementation of the project. National Hydraulic Research Institute of Malaysia (NAHRIM) as one of the four agencies that have been implemented Malaysia’s BDA Proof-of-Concept (POC) initiative is no exception to these misconceptions. In this paper, we will discuss the misunderstandings and challenges faced throughout our BDA project, in encouraging and increasing the awareness of the implementation of BDA in Government sector.