Architecting Data-Driven Applications: From Architectural Design to the Data Quality

Abughazala, Moamin; Muccini, Henry; Sharaf, Mohammad

doi:10.2139/ssrn.4382947

Cited by 2 publications

(2 citation statements)

References 67 publications

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“…As data moves through its lifecycle, issues of access control, privacy preservation, and regulatory compliance become paramount. Challenges also arise in determining the optimal retention periods for different types of data and managing the secure deletion of obsolete information [93], [94]. In the dynamic landscape of big data analytics, developing and adhering to comprehensive data lifecycle management strategies that align with organizational goals, industry regulations, and ethical considerations is essential to maximize the value of data while minimizing associated risks and inefficiencies.…”

Section: Data Lifecycle Managementmentioning

confidence: 99%

Tackling security and privacy challenges in the realm of big data analytics

Janet Ngesa

2023

World J. Adv. Res. Rev.

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As organizations increasingly harness the power of big data analytics to derive insights and drive decision-making, the paramount concerns of security and privacy have come to the forefront. This paper presents a comprehensive framework for addressing the multifaceted challenges of big data security and privacy. Drawing on a synthesis of cutting-edge technologies, encryption methods, and access control mechanisms, our approach aims to fortify the entire big data lifecycle. The paper delves into innovative strategies for secure data storage, transmission, and processing, ensuring that sensitive information is shielded from unauthorized access or malicious attacks. Additionally, the framework incorporates robust privacy-preserving techniques, including anonymization and differential privacy, to uphold individual confidentiality. Through a meticulous analysis of current trends, emerging threats, and regulatory landscapes, this paper not only provides theoretical insights but also practical guidelines for organizations seeking to navigate the intricate landscape of big data while safeguarding the integrity, security, and privacy of the vast datasets at their disposal.

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Section: Data Lifecycle Managementmentioning

confidence: 99%

Tackling security and privacy challenges in the realm of big data analytics

Janet Ngesa

2023

World J. Adv. Res. Rev.

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“…The interest data for such a request is removed from the defined sets and is processed in the appropriate sequence of scheduled operations on the nodes. Therefore, the data of the digital microscopy frame processing application is combined during the addition of digital sub-blocks and the corresponding viewing [4,18], and next it is sent to the client.…”

Section: Introductionmentioning

confidence: 99%

Socket performance influence on data processing intensity in a virtual machine cluster with heterogeneous conditions.

Melnyk,

Bahnіuk,

Roiko

et al. 2024

cit

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The paper presents the dependences of data processing in heterogeneous conditions taking into account the impact of socket performance. As high-performance, sockets are proposed on the virtual interface architecture to use a component basis in order to support the application performance for intensive data processing. High-performance applications, using the traditional Linux-based TCP/IP interface, require guarantees of performance and its scalability to adapt for heterogeneous networks. In case of using highly effective protocols for their operation, some additional methods should be used at the user level, including for sockets on the virtual interface architecture. The limitation on the high-performance socket layers is tyed with the application developing completion to full performance salvation during the TCP/IP data transfer process. There also revealed that small-block load balancing has been found to increase heterogeneous network adaptation

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Architecting Data-Driven Applications: From Architectural Design to the Data Quality

Cited by 2 publications

References 67 publications

Tackling security and privacy challenges in the realm of big data analytics

Tackling security and privacy challenges in the realm of big data analytics

Socket performance influence on data processing intensity in a virtual machine cluster with heterogeneous conditions.

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