Big data challenges for resource-constrained organizations in a developing economy

Sultana, Hafiza; Zaman, Rajeeb Bin; Zahan, Muslima

doi:10.1080/15228053.2020.1807173

Cited by 2 publications

(1 citation statement)

References 34 publications

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“…Big Data integration in smart cities is hindered by a diverse population and a lack of infrastructure, according to the [10] study's conclusions. According to [10] • Both [14], [19] studies concentrated on the developing countries. The aim of [14] study was to show the knowledge, attitude, and issues associated with big data analytics from the perspective of IT employees in a developing country.…”

Section: The Details Of the Reviewed Articlesmentioning

confidence: 99%

Challenges and Obstacles Facing Data in the Big Data Environment

Aloufi¹,

Abdulaziz

2022

Comm. Math. Appl.

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Big data is dubbed "today's digital oil" and the "new raw resource of the twenty-first century". BD is synonymous with the future of innovation, competition, and productivity. It can produce and find corporate value by analyzing data in ways that older methodologies could not. Regardless of its benefits, the development of big data continues to encounter various barriers, the most important of which are security and privacy concerns. As a result, this study is motivated by the need to address and evaluate big data challenges. Thus, by comparing and contrasting big data difficulties with available and potential solutions, users, developers, and businesses can find pertinent and timely responses to specific dangers, resulting in the best possible big data-based services. The objective of this essay is to highlight the inherent challenges of big data and some essential strategies for overcoming them.The purpose of this article was to extract and analyze significant works in order to contribute to the corpus of literature by emphasizing many critical difficulties in the big data domain and throwing light on how these challenges affect a range of domains, including users, sites, and business. Many issues such as data privacy, information sharing, failures in big data technologies and infrastructure, poor data quality management, managers and policymakers' inability to learn and adapt, the absence of government policies and plans, the lack of successfully implemented big data analytics projects, and the lack of human experience are among the most frequently mentioned issues. Obstacles also exist in the areas of real-time data collection, as well as real-time data processing and visualization, among others.By combining previously identified solutions, this research addressed these concerns. The consequences for both researchers and practitioners have been discussed. Aiming to help scholars gain a comprehensive understanding of these issues and confirm the approaches used to address them, this study's theoretical focus is broad. This study uses tried-and-true solutions to overcome these obstacles. Business and individuals using big data analytics systems will benefit from these solutions.

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