Big Data in Healthcare: Challenges and Promise

Kale, Siddharth; Tamakuwala, Harsh; Vijayakumar, V.; Yang, Longzhi; Kshatriya, Bharat S. Rawal

doi:10.1007/978-981-32-9889-7_1

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…These systems rely on hundreds of sensor nodes and other devices which continuously sense and stream readings of various parameters rendering large volumes of data, which is known as Big Data [54]. The term Big Data describes a massive volume of complex and different types of structured and unstructured data that accumulate in a relatively high velocity [55]. Mining and analysing big data has a significant role in providing a rich source of information about smart cities' utilities and citizens' activities, providing more efficient management, better services and sustainable development [56].…”

Section: Smart Cities As Large-scale Cpssmentioning

confidence: 99%

Data quality challenges in large-scale cyber-physical systems: A systematic review

Alwan

Ciupala

Brimicombe

et al. 2022

Information Systems

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Section: Smart Cities As Large-scale Cpssmentioning

confidence: 99%

Data quality challenges in large-scale cyber-physical systems: A systematic review

Alwan

Ciupala

Brimicombe

et al. 2022

Information Systems

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“…The usage of unreliable data from diverse sources, valueless, and irrelevance of data may lead to unnecessary effort and cost for companies [8]. Unstructured data usability is a major concern for analytical applications because these applications are not able to adequately use unstructured data for analytics [9]. It is vital to improve the unstructured data usability for better unstructured data analytics.…”

Section: Introductionmentioning

confidence: 99%

Development of Usability Enhancement Model for Unstructured Big Data Using SLR

2021

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Unstructured text contains valuable information for a range of enterprise applications and informed decision making. Text analytics is used to extract valuable insights from unstructured big data. Among the most significant challenges of text analytics, quality and usability are critical affecting the outcome of the analytical process. The enhancement in usability is important for the exploitation of unstructured data. Most of the existing literature focuses on the usability of structured data as compared to unstructured data whereas big data usability has been discussed merely in context of its assessment. The existing approaches do not provide proper guidelines on usability enhancement of unstructured data. In this study, a rigorous systematic literature review, using PRISMA framework, has been conducted to develop a model enhancing the usability of unstructured data and bridging the research gap. The recent approaches and solutions for text analytics have been investigated thoroughly. Furthermore, it identifies the usability issues of unstructured text data and their consequences on data preparation for analytics. Defining the usability dimensions for unstructured big data, identification of the usability determinants, and developing a relationship between usability dimension and determinants to derive usability rules are the significant contribution of this research, and are integrated to formulate the model. The proposed usability enhancement model is the major outcome of the study. It would contribute to making unstructured data usable and facilitating the data preparation activities with more valuable data that eventually improves the analytical process.

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