scholarly journals Using Big Data Technology to Analyze the Development Direction of Internal Audit

2020 ◽  
Vol 1648 ◽  
pp. 042040
Author(s):  
Zuhui Wang
2021 ◽  
Vol 2050 (1) ◽  
pp. 012016
Author(s):  
Yong Wen

Abstract The development of digital industrialization has promoted the continuous emergence of new industries, new formats and new models, and has also promoted the transformation of the traditional internal audit model to digital and intelligent. Big data, cloud computing, XBRL, artificial intelligence and other digital technologies are important means to achieve full audit coverage, big data audit has become a hot topic in the current audit field, relevant literature mainly focuses on the impact of big data on traditional audit concepts and audit methods, the impact and risks of big data technology on informatization audits, and how the auditing community responds. However, the research on the integration of big data technology and XBRL technology into continuous internal auditing is relatively rare. Based on the introduction of three XBRL continuous internal audit models, this article analyzes the continuous internal audit process of the XBRL information system, and discusses the application of big data technology in XBRL continuous internal audit.


2014 ◽  
Vol 971-973 ◽  
pp. 1590-1593 ◽  
Author(s):  
Chun Yan Xue

The core objective of Big Data technology is trying to dig out valuable information from massing huge variety of data structures. In order to achieve these goals, Big Data technology must be combined with machine learning. The uniqueness of Big Data has also brought unprecedented challenges to machine learning, in order to cope with these challenges machine learning should focus on the development of semi-supervised learning method, integrated learning with device integration and transfer learning method.


Author(s):  
Yu Zhang ◽  
Yan-Ge Wang ◽  
Yan-Ping Bai ◽  
Yong-Zhen Li ◽  
Zhao-Yong Lv ◽  
...  

2020 ◽  
Vol 12 (13) ◽  
pp. 5470 ◽  
Author(s):  
Antonio Matas-Terrón ◽  
Juan José Leiva-Olivencia ◽  
Pablo Daniel Franco-Caballero ◽  
Francisco José García-Aguilera

Big Data technology can be a great resource for achieving the Sustainable Development Goals in a fair and inclusive manner; however, only recently have we begun to analyse its impact on education. This research goal was to analyse the psychometric characteristics of a scale to assess opinions that educators in training have about Big Data besides their related emotions. This is important, as it will be the educators of the future who will have to manage with Big Data at school. A nonprobability sample of 337 education students from Peru and Spain was counted. Internal consistency, as well as validity, were analysed through exploratory and confirmatory factorial analysis. The results show good psychometric values, highlighting as relevant a latent structure of six factors that includes emotional and cognitive dimensions. As a result, the profile defining the participants in relation to Big Data was identified. Finally, the implications of the Big Data for Inclusive Education in a sustainable society are discussed.


2021 ◽  
Vol 1881 (4) ◽  
pp. 042036
Author(s):  
Jiao Tan ◽  
Yonghong Ma ◽  
Ke Men ◽  
Jing Lei ◽  
Hairui Zhang ◽  
...  

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