Medicine is constantly generating new imaging data, including data from basic research, clinical research, and epidemiology, from health administration and insurance organizations, public health services, and non-conventional data sources such as social media, Internet applications, etc. Healthcare professionals have gained from the integration of big data in many ways, including new tools for decision support, improved clinical research methodologies, treatment efficacy, and personalized care. Finally, there are significant advantages in saving resources and reallocating them to increase productivity and rationalization. In this paper, we will explore how big data can be applied to the field of digital health. We will explain the features of health data, its particularities, and the tools available to use it. In addition, a particular focus is placed on the latest research work that addresses big data analysis in the health domain, as well as the technical and organizational challenges that have been discussed. Finally, we propose a general strategy for medical organizations looking to adopt or leverage big data analytics. Through this study, healthcare organizations and institutions considering the use of big data analytics technology, as well as those already using it, can gain a thorough and comprehensive understanding of the potential use, effective targeting, and expected impact.

https://www.mdpi.com/2504-2289/7/2/64/pdf?version=1680165823

Enhancing Digital Health Services with Big Data Analytics


Purpose
Recently, Vietnamese enterprises have begun to realize the potential benefits of big data and harnessing all of the data they have been creating. Experiencing the crisis time of the COVID-19 pandemic, they could apprehend more and more benefits of digitalizing trend. However, a big problem for many Vietnamese enterprises is understanding where to begin in implementing big data and analytics. The study’s main objective is to investigate the impact factors of implementing big data and analytics in Vietnamese enterprises post-COVID-19 pandemic.


Design/methodology/approach
The study is exploratively conducted with a quantitative survey approach and uses purposive techniques in collecting data. The sample focuses on Vietnamese enterprises which have experience with big data and analytics.


Findings
This study intended to highlight some aspects to consider when implementing big data and analytics in Vietnamese enterprises post-COVID-19 pandemic.


Originality/value
To the best of the author’s knowledge, this study is the first academic paper to study Vietnamese enterprises’ considerations of big data and analytics post-COVID-19 pandemic.


Vietnamese enterprises’ considerations of big data and analytics implementation post-COVID-19 pandemic

Analysis of the feasibility and advantages of using big data technology for English translation

Huge amounts of digital data are continuously generated and collected from different sources, such as sensors, cameras, in-vehicle infotainment, smart meters, mobile devices, social media platforms, and web applications and services [...] 

https://www.mdpi.com/2504-2289/7/2/104/pdf?version=1685426053

Perspectives on Big Data, Cloud-Based Data Analysis and Machine Learning Systems

The Online Roadshow, a new type of web application, is a digital marketing approach that aims to maximize contactless business engagement. It leverages web computing to conduct interactive game sessions via the internet. As a result, massive amounts of personal data are generated during the engagement process between the audience and the Online Roadshow (e.g., gameplay data and clickstream information). The high volume of data collected is valuable for more effective market segmentation in strategic business planning through data-driven processes such as web personalization and trend evaluation. However, the data storage and processing techniques used in conventional data analytic approaches are typically overloaded in such a computing environment. Hence, this paper proposed a new big data processing framework to improve the processing, handling, and storing of these large amounts of data. The proposed framework aims to provide a better dual-mode solution for processing the generated data for the Online Roadshow engagement process in both historical and real-time scenarios. Multiple functional modules, such as the Application Controller, the Message Broker, the Data Processing Module, and the Data Storage Module, were reformulated to provide a more efficient solution that matches the new needs of the Online Roadshow data analytics procedures. Some tests were conducted to compare the performance of the proposed frameworks against existing similar frameworks and verify the performance of the proposed framework in fulfilling the data processing requirements of the Online Roadshow. The experimental results evidenced multiple advantages of the proposed framework for Online Roadshow compared to similar existing big data processing frameworks.

/pdf/a-new-big-data-processing-framework-for-the-online-roadshow-njmz8xel.pdf

A New Big Data Processing Framework for the Online Roadshow

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.

/pdf/explore-big-data-analytics-applications-and-opportunities-a-piu2ped9.pdf

Rasha Moh’d Sadeq Abdin

Papers

Explore Big Data Analytics Applications and Opportunities: A Review