Analysis of the Impact of Big Data Technology on Corporate Profitability

2021 ◽  
pp. 427-437
Author(s):  
Changsheng Bao
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.


Author(s):  
Janet Chan

Internet and telecommunications, ubiquitous sensing devices, and advances in data storage and analytic capacities have heralded the age of Big Data, where the volume, velocity, and variety of data not only promise new opportunities for the harvesting of information, but also threaten to overload existing resources for making sense of this information. The use of Big Data technology for criminal justice and crime control is a relatively new development. Big Data technology has overlapped with criminology in two main areas: (a) Big Data is used as a type of data in criminological research, and (b) Big Data analytics is employed as a predictive tool to guide criminal justice decisions and strategies. Much of the debate about Big Data in criminology is concerned with legitimacy, including privacy, accountability, transparency, and fairness. Big Data is often made accessible through data visualization. Big Data visualization is a performance that simultaneously masks the power of commercial and governmental surveillance and renders information political. The production of visuality operates in an economy of attention. In crime control enterprises, future uncertainties can be masked by affective triggers that create an atmosphere of risk and suspicion. There have also been efforts to mobilize data to expose harms and injustices and garner support for resistance. While Big Data and visuality can perform affective modulation in the race for attention, the impact of data visualization is not always predictable. By removing the visibility of real people or events and by aestheticizing representations of tragedies, data visualization may achieve further distancing and deadening of conscience in situations where graphic photographic images might at least garner initial emotional impact.


2020 ◽  
Vol 214 ◽  
pp. 01004
Author(s):  
Wang Yang

”Big data” is the product of the integration of the highly developed Internet innovation function and various economic fields in today’s society. The development of “big data” is bound to bring significant changes in the economic development of today’s society. Taking HUA WEI technologies co., LTD., financial aspects based on the development of big data, found big data technology in the application process of the impact of the financial accounting, this era of big data work flow for the company in China, the impact of financial decision-making and financial personnel, and the company response to this phenomenon and make a change, and to analyze its causes and solutions. This electronic document is a “live” template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document.


CONVERTER ◽  
2021 ◽  
pp. 270-281
Author(s):  
Chenguang Zhang, Guifa Teng

Objectives: In order to alleviate the impact of COVID-19 on China's poverty alleviation work, this paper proposesa performance evaluation method and a recommendation algorithm for poverty indicator system suitable forChina's national conditions based on big data technology. Methods: The evaluation method combines the preciseadvantages of Bayesian classifier and the full-volume processing characteristics of big data to comprehensivelyevaluate the past poverty alleviation achievements. The recommendation algorithm takes the poverty alleviationdata over the years as the research object and realizes the construction method of the indicator system in therelative poverty stage. Results: The comparison with Pearson's correlation coefficient shows that the newevaluation method has more accurate confidence calculation ability. And compared with the classic ALSrecommendation algorithm, the new recommendation algorithm has a more scientific and reasonablerecommendation effect. Conclusions: Finally, the paper proposes relevant suggestions for the next stage of policyformulation, proves that medical and health conditions play an important role in supporting poverty alleviation.


2022 ◽  
Vol 2022 ◽  
pp. 1-12
Author(s):  
Qin Yang

The arrival of the big data era not only provides corresponding technical support for the development of Educational Networking but also promotes the acceleration of Educational Networking. Therefore, this paper puts forward the research on the impact of big data on the development of education network and constructs a Bayesian knowledge tracking model to collect and analyze the behavior data of teachers and learners in network education. The experimental results show that big data technology provides greater development space for Education Networking. Its market scale has reached 502.47 billion yuan in 2021, and there is a trend of continuous growth. At the same time, the increase in the number of users also makes its teaching content richer and teaching methods more diversified and personalized. And, through the analysis of relevant data, learners and teachers can more comprehensively and truly understand their own level, achieve the purpose of accurate assistance to learners and teachers, and help learners and teachers find their own problems and make targeted adjustments. In addition, the campus intelligent management system based on big data technology can achieve the purpose of multipurpose and information management.


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