Analysis of multidisciplinary limits, challenges, and considerations in big data storage: recommendations for fiscal surveillance and control

Abstract

An increasingly digitized world demands efficient information management strategies. Implementing processes for data lifecycle management, from its collection to its end user consumption, is important, as it is a process that requires significant effort and challenges in all stages of Big Data (BD). As part of BD, Big Data Storage (BDS) allows for efficient retrieval and analysis of large amounts of data in terms of storing information efficiently. An efficient BDS can be supported by Scalability, high performance, flexibility, security, data governance, cost-effectiveness, and the capacity to handle multi-structured data. This article presents a multidisciplinary view of the limits, challenges, and considerations currently found in BDS conducted by a literature review. The systematic literature review identified current problems in BDS, such as volume, velocity, variety, veracity, and data security. Based on the limits, challenges, and considerations of BDS found in the review and synthesized in multiple areas, a list of BDS recommendations was identified and tailored to the field of Fiscal Surveillance and Control. Adopting modern technologies, including cloud computing, edge computing, and advanced technologies such as blockchain and artificial intelligence, can improve data security and efficiency. An organization intending to implement an internal or external Fiscal surveillance and control system may consider these recommendations in BDS to manage their information more efficiently.