Big Data Maturity Assessment Models: A Systematic Literature Review
Abstrak
Big Data and analytics have become essential factors in managing the COVID-19 pandemic. As no company can escape the effects of the pandemic, mature Big Data and analytics practices are essential for successful decision-making insights and keeping pace with a changing and unpredictable marketplace. The ability to be successful in Big Data projects is related to the organization’s maturity level. The maturity model is a tool that could be applied to assess the maturity level across specific key dimensions, where the maturity levels indicate an organization’s current capabilities and the desirable state. Big Data maturity models (BDMMs) are a new trend with limited publications published as white papers and web materials by practitioners. While most of the related literature might not have covered all of the existing BDMMs, this systematic literature review (SLR) aims to contribute to the body of knowledge and address the limitations in the existing literature about the existing BDMMs, assessment dimensions, and tools. The SLR strategy in this paper was conducted based on guidelines to perform SLR in software engineering by answering three research questions: (1) What are the existing maturity assessment models for Big Data? (2) What are the assessment dimensions for Big Data maturity models? and (3) What are the assessment tools for Big Data maturity models? This SLR covers the available BDMMs written in English and developed by academics and practitioners (2007–2022). By applying a descriptive qualitative content analysis method for the reviewed publications, this SLR identified 15 BDMMs (10 BDMMs by practitioners and 5 BDMMs by academics). Additionally, this paper presents the limitations of existing BDMMs. The findings of this paper could be used as a grounded reference for assessing the maturity of Big Data. Moreover, this paper will provide managers with critical insights to select the BDMM that fits within their organization to support their data-driven decisions. Future work will investigate the Big Data maturity assessment dimensions towards developing a new Big Data maturity model.
Artikel Ilmiah Terkait
Jie Sheng Xiaojun Wang Zaheer Khan + 1 lainnya
2 November 2020
Although scholars in management recognize the value of harnessing big data to understand, predict and respond to future events, there remains little or very limited overview of how various analytics techniques can be harnessed to provide the basis for guiding scholars in studying contemporary management topics and global grand challenges raised by the COVID-19 pandemic In this Methodology Corner, we present a review of the methodological innovations in studying big data analytics and how they can be better utilized to examine contemporary organizational issues We provide insights on methods in descriptive/diagnostic, predictive and prescriptive analytics, and how they can be leveraged to study 'black swan' events such as the COVID-19-related global crisis and its aftermath's implications for managers and policymakers
N. Damer L. Abualigah Rasha Moh’d Sadeq Abdin + 4 lainnya
14 Desember 2022
Big data applications and analytics are vital in proposing ultimate strategic decisions. The existing literature emphasizes that big data applications and analytics can empower those who apply Big Data Analytics during the COVID-19 pandemic. This paper reviews the existing literature specializing in big data applications pre and peri-COVID-19. A comparison between Pre and Peri of the pandemic for using Big Data applications is presented. The comparison is expanded to four highly recognized industry fields: Healthcare, Education, Transportation, and Banking. A discussion on the effectiveness of the four major types of data analytics across the mentioned industries is highlighted. Hence, this paper provides an illustrative description of the importance of big data applications in the era of COVID-19, as well as aligning the applications to their relevant big data analytics models. This review paper concludes that applying the ultimate big data applications and their associated data analytics models can harness the significant limitations faced by organizations during one of the most fateful pandemics worldwide. Future work will conduct a systematic literature review and a comparative analysis of the existing Big Data Systems and models. Moreover, future work will investigate the critical challenges of Big Data Analytics and applications during the COVID-19 pandemic.
Matti Mäntymäki A. Dhir Sayantan Khanra
17 Maret 2020
ABSTRACT Understanding the developmental trajectories of big data analytics in the corporate context is highly relevant for information systems research and practice. This study presents a comprehensive bibliometric analysis of applications of big data analytics in enterprises. The sample for this study contained a total of 1727 articles from the Scopus database. The sample was analyzed with techniques such as bibliographic coupling, citation analysis, co-word analysis, and co-authorship analysis. Findings from the co-citation analysis identified four major thematic areas in the extant literature. The evolution of these thematic areas was documented with dynamic co-citation analysis.
Phaik Kin Cheah Mohammad Falahat Jayamalathi Jayabalan + 2 lainnya
26 Desember 2022
The unprecedented COVID-19 pandemic, together with globalization and advanced technologies, has drastically changed the business environment and forced companies to become more innovative and agile in the way they run their business and respond to the needs and wants of customers. Survival highly depends on the adaptability of SMEs to this ever-changing complex dynamic environment by taking steps in implementing Big Data Analytics as the next frontier for innovation, competition, productivity, and value creation. Based on the grounded theory, this study employed a qualitative method via focus group discussion. Focus groups were conducted with 14 government agencies, SMEs associations, business owners, Chief Operating Officers (CEOs), academic and industrial experts and directors of SMEs in Malaysia. The study revealed the challenges of Malaysian SMEs in adopting Big Data Analytics Capability, presents the criticality of Big Data Analytics Capability to overcome the identified challenges, and develops a BDA Capability Ecosystem Model that integrates the internal enablers, external barriers and support to explain the adoption of BDA Capability for value creation and support the decision-making process. This paper is followed by some policy suggestions for companies’ owners, policymakers, government agencies, universities, and SMEs. This study directly impacts Malaysia’s economy as a whole by addressing Malaysia’s Shared Prosperity Vision 2030. This research contributes to industries that are still in the low value added category with low adoption of technology. Furthermore, it will ultimately lead to the realization of SMEs as ‘game changers’ to transition the economy to a high-income nation. This study proposes a model that could help SMEs improve their value creation performance, directly influencing the country’s GDP and employability.
A. Aljumah M. Nuseir Md. Mahmudul Alam
24 Juni 2021
PurposeThe aim of the study is to examine the impact of the big data analytics capabilities (BDAC) on the organizational performance. The study also examines the mediating role of ambidexterity and the moderating role of business value of big data (BVBD) analytics in the relationship between the big data analytics capabilities and the organizational performance.Design/methodology/approachThis study collected primary data based on a questionnaire survey among the large manufacturing firms operating in UAE. A total of 650 questionnaires were distributed among the manufacturing firms and 295 samples were used for final data analysis. The survey was conducted from September to November in 2019, and data were analyzed based on partial least squares structural equation modeling (PLS-SEM).FindingsThe big data analysis (BDA) scalability is supported by the findings on the performance of firm and its determinants such as system, value of business and quality of information. The roles of business value as a moderator and ambidexterity as mediator are found significant. The results reveal that there is a need for managers to consider the business value and quality dynamics as crucial strategic objectives to achieve high performance of the firm.Research limitations/implicationsThe study has significant policy implication for practitioners and researchers for understanding the issues related to big data analytics.Originality/valueThis is an original study based on primary data from UAE manufacturing firms.
Daftar Referensi
0 referensiTidak ada referensi ditemukan.
Artikel yang Mensitasi
0 sitasiTidak ada artikel yang mensitasi.