scholarly journals Big Data Application and its Impact on Education

2020 ◽  
Vol 15 (17) ◽  
pp. 36
Author(s):  
Shakir Khan ◽  
Salihah Alqahtani
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Educational Data Mining ◽  
Time Interval ◽  
Data Application ◽  
Big Data Application ◽  
Education Process

Big data is employed in widely different fields; we here study how education uses big data. We review the literature of the research about big data in education in the time interval from 2010 to 2020 then review the process of big educational data mining, the tools, and the applications of big data in education. This paper, with the help of these applications, explores the idea to improve the education process. Two methods are applied to validate education process and many parameters are discussed to complete the research.

scholarly journals Research on the Personal Privacy in the Health Big Data

2020 ◽  
Vol 214 ◽  
pp. 03022
Author(s):  
Cangcang JIA ◽  
Han LIU
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Conflicts Of Interest ◽  
Personal Privacy ◽  
Conflict Of Interests ◽  
Data Prediction ◽  
Data Application ◽  
Digital Monitoring ◽  
Big Data Application ◽  
Big Data Technology

Data mining, data prediction and all-round digital monitoring of health big data make the dilemma of personal privacy control prominent. The weakening of the control of personal privacy by big data technology, the people’s data belief, the diversity of interests and the conflict of interests are the main causes of the problem of personal privacy in the context of the application of health big data. Therefore, in the application of health big data, the solution to the problem of personal privacy in the context of health big data application is to enhance the value transparency of big data technology, return and reshape humanism, and explore common values to reduce conflicts of interest.

scholarly journals Big Data Analytic Framework for Organizational Leverage

2021 ◽  
Vol 11 (5) ◽  
pp. 2340
Author(s):  
Sanjay Mathrani ◽  
Xusheng Lai
Keyword(s):  
Big Data ◽  
Web Sites ◽  
Big Data Analytics ◽  
Building Blocks ◽  
Application Service ◽  
Data Application ◽  
Other Information ◽  
Big Data Application ◽  
Diverse Data ◽  
Framework System

Web data have grown exponentially to reach zettabyte scales. Mountains of data come from several online applications, such as e-commerce, social media, web and sensor-based devices, business web sites, and other information types posted by users. Big data analytics (BDA) can help to derive new insights from this huge and fast-growing data source. The core advantage of BDA technology is in its ability to mine these data and provide information on underlying trends. BDA, however, faces innate difficulty in optimizing the process and capabilities that require merging of diverse data assets to generate viable information. This paper explores the BDA process and capabilities in leveraging data via three case studies who are prime users of BDA tools. Findings emphasize four key components of the BDA process framework: system coordination, data sourcing, big data application service, and end users. Further building blocks are data security, privacy, and management that represent services for providing functionality to the four components of the BDA process across information and technology value chains.

Preliminary Benefits of Big Data in the Construction Industry: A Case Study

2022 ◽  
pp. 1-11
Author(s):  
Bernard Tuffour Atuahene ◽  
Sittimont Kanjanabootra ◽  
Thayaparan Gajendran
Keyword(s):  
Big Data ◽  
Construction Industry ◽  
Construction Projects ◽  
Big Data Applications ◽  
Data Application ◽  
Construction Firm ◽  
Big Data Application ◽  
Tangible Benefit ◽  
Design Construction

Big data applications consist of i) data collection using big data sources, ii) storing and processing the data, and iii) analysing data to gain insights for creating organisational benefit. The influx of digital technologies and digitization in the construction process includes big data as one newly emerging digital technology adopted in the construction industry. Big data application is in a nascent stage in construction, and there is a need to understand the tangible benefit(s) that big data can offer the construction industry. This study explores the benefits of big data in the construction industry. Using a qualitative case study design, construction professionals in an Australian Construction firm were interviewed. The research highlights that the benefits of big data include reduction of litigation amongst projects stakeholders, enablement of near to real-time communication, and facilitation of effective subcontractor selection. By implication, on a broader scale, these benefits can improve contract management, procurement, and management of construction projects. This study contributes to an ongoing discourse on big data application, and more generally, digitization in the construction industry.

scholarly journals Federated Learning in Big Data Application and Sharing

2020 ◽  
Author(s):  
Jing Yang ◽  
Quan Zhang ◽  
Kunpeng Liu ◽  
Peng Jin ◽  
Guoyi Zhao
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
The State ◽  
Ideal Model ◽  
Local Data ◽  
Data Safety ◽  
Big Data Applications ◽  
Data Application ◽  
Big Data Application ◽  
Uniform Model

In recent years, electricity big data has extensive applications in the grid companies across the provinces. However, certain problems are encountered including, the inability to generate an ideal model using the isolated data possessed by each company, and the priority concerns for data privacy and safety during big data application and sharing. In this pursuit, the present research envisaged the application of federated learning to protect the local data, and to build a uniform model for different companies affiliated to the State Grid. Federated learning can serve as an essential means for realizing the grid-wide promotion of the achievements of big data applications, while ensuring the data safety.

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