Digital preservation at Big Data scales: proposing a step-change in preservation system architectures

Gerrard, D.; Mooney, James E.; Thompson, Dave

doi:10.1108/lht-06-2017-0122

Cited by 15 publications

(7 citation statements)

References 17 publications

(18 reference statements)

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“…Thus, as these firms attempt to innovate and adopt emergent technologies such as blockchain, they must first determine if these technologies are in conflict with the GDPR if they involve data management. However, blockchain is also a technology that shares the privacy and protection of all data in the same exact way that the GDPR seeks to enforce (Gerrard, Mooney, & Thompson, 2018). Hence, blockchain and the GDPR may actually be ideally suited for each other.…”

Section: Discussionmentioning

confidence: 99%

“…The observation is such that big data that focuses on marketing will especially damage marketing driven solutions because anonymization of the data prevents personalization of the data for marketing purposes. Big data consists of enormous amounts of data that has been amassed for ulterior purposes such that it is characterized by three specific elements: 1) volume which refers to relatively less dense and unstructured information, 2) velocity which refers to the rapid nature with which such data builds up and 3) variety which refers to the sheer diversity of data forms, types and information that is collected (Gerrard, Mooney, & Thompson, 2018). Understanding how these three qualities intersect produces improved understanding of what big data is and what it can accomplish if structured appropriately as the figure below demonstrates: Figure 1.…”

Section: What Is Big Datamentioning

confidence: 99%

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The European Union’s GDPR and Its Effect on Data-Driven Marketing Strategies

Alfayad¹

2020

IJMS

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This research paper analyzes the developing effect that the European Union’s (EU) recently developed General Data Protection Regulation (GDPR) will have on the marketing strategies of firms that rely on big data. Big data is identified as consisting of data and data analytics involving a huge volume of data, a diverse variety of data, and a high velocity of data capture and collection. This analysis begins with some discussion of the concept of big data and follows this up with overviews of both the GDPR and big data use in the marketplace. The EU replaced its older Data Protection Directive or DPD with the GDPR. The GDPR consists of a series of chapters and articles that require, among other things, consent to collect and store data, the anonymization of data, announcement in 72 hours of a data breach, provision of encryption and the identification of a Data Protection Officer. Marketing and the marketing function can implement emergent technologies that augment big data and its analysis while simultaneously achieving compliance with regulatory frameworks like the GDPR. These marketing related solutions are those such as blockchain marketing applications like Brave Browser and Blockstack among others. The report also examines the way in which enterprises use big data in their marketing strategies and how they are affected by it now that it has come into effect. Some of the more marketing-oriented uses and applications of big data are found in sophisticated loyalty programs, demand forecasting and customization either of experience or product/service. This study also offers some final recommendations related to GDPR compliant marketing strategies. These include the development of a comprehensive program to purchase consumer data directly from consumers and the introduction of blockchain as a means to facilitate a smoother transition to GDPR compliance.

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Section: Discussionmentioning

confidence: 99%

Section: What Is Big Datamentioning

confidence: 99%

The European Union’s GDPR and Its Effect on Data-Driven Marketing Strategies

Alfayad¹

2020

IJMS

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“…The contexts and the most frequently addressed issues about the placement of the VM in a cloud environment are overviewed and distinguished. In the cloud environment, virtualization is one of the main technologies (Gerrard et al , 2018). It divides services and resources from the fundamental physical delivery environment (Dalvandi et al , 2015).…”

Section: Review Of Selected Papersmentioning

confidence: 99%

Virtual machine placement mechanisms in the cloud environments: a systematic review

Zhuang

Ghouchani

2020

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Purpose Virtual machines (VMs) are suggested by the providers of cloud services as the services for the users over the internet. The consolidation of VM is the tactic of the competent and smart utilization of resources from cloud data centers. Placement of a VM is one of the significant issues in cloud computing (CC). Physical machines in a cloud environment are aware of the way of the VM placement (VMP) as the mapping VMs. The basic target of placement of VM issue is to reduce the physical machines' items that are running or the hosts in cloud data centers. The VMP methods have an important role in the CC. However, there is no systematic and complete way to discuss and analyze the algorithms. The purpose of this paper is to present a systematic survey of VMP techniques. Also, the benefits and weaknesses connected with selected VMP techniques have been debated, and the significant issues of these techniques are addressed to develop the more efficient VMP technique for the future. Design/methodology/approach Because of the importance of VMP in the cloud environments, in this paper, the articles and important mechanisms in this domain have been investigated systematically. The VMP mechanisms have been categorized into two major groups, including static and dynamic mechanisms. Findings The results have indicated that an appropriate VMP has the capacity to decrease the resource consumption rate, energy consumption and carbon emission rate. VMP approaches in computing environment still need improvements in terms of reducing related overhead, consolidation of the cloud environment to become an extremely on-demand mechanism, balancing the load between physical machines, power consumption and refining performance. Research limitations/implications This study aimed to be comprehensive, but there were some limitations. Some perfect work may be eliminated because of applying some filters to choose the original articles. Surveying all the papers on the topic of VMP is impossible, too. Nevertheless, the authors are trying to present a complete survey over the VMP. Practical implications The consequences of this research will be valuable for academicians, and it can provide good ideas for future research in this domain. By providing comparative information and analyzing the contemporary developments in this area, this research will directly support academics and working professionals for better knowing the growth in the VMP area. Originality/value The gathered information in this paper helps to inform the researchers with the state of the art in the VMP area. Totally, the VMP's principal intention, current challenges, open issues, strategies and mechanisms in cloud systems are summarized by explaining the answers.

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“…In such a case, are they ready to participate in high-volume data and to deal with large-scale data investments to minimise the risks associated with them? Similarly, researchers [22] have highlighted problems in the big data age. They have found that the main problem in digital preservation was the storage of more massive, more complex datasets and more need-based metadata.…”

Section: Literature Reviewmentioning

confidence: 99%

Performance-based evaluation of academic libraries in the big data era

Islam

Ahmad

Rafi

et al. 2020

Journal of Information Science

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The concept of big data has been extensively considered as a technological modernisation in organisations and educational institutes. Thus, the purpose of this study is to determine whether the modified technology acceptance model (MTAM) is viable for evaluating the performance of librarians in the use of big data analytics in academic libraries. This study used an empirical research method for collecting data from 211 librarians working in Pakistan’s universities. On the basis of the findings of the MTAM analysis by structural equation modelling, the performances of the academic libraries were comprehended through the process of big data. The main influential components of the performance analysis in this study were the big data analytics capabilities, perceived ease of access and the usefulness of big data practices in academic libraries. Subsequently, the utilisation of big data was significantly affected by skills, perceived ease of access and the usefulness of academic libraries. The results also suggested that the various components of the academic libraries lead to effective organisational performance when linked to big data analytics.

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Digital preservation at Big Data scales: proposing a step-change in preservation system architectures

Cited by 15 publications

References 17 publications

The European Union’s GDPR and Its Effect on Data-Driven Marketing Strategies

The European Union’s GDPR and Its Effect on Data-Driven Marketing Strategies

Virtual machine placement mechanisms in the cloud environments: a systematic review

Performance-based evaluation of academic libraries in the big data era

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