Research on University Accounting Teaching Innovation Based on big data

2021 ◽  
Vol 7 (5) ◽  
pp. 4384-4392
Author(s):  
Hongxuan Ma
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Accounting Education ◽  
Financial Accounting ◽  
Teaching Innovation ◽  
Teaching Reform ◽  
The University ◽  
Education In China ◽  
Education Concept ◽  
Big Data Technology

Objectives: With the arrival of the era of big data, the use of cloud computing technology has the characteristics of large capacity, variety and speed. Big data makes the teaching of financial accounting more convenient and efficient. Methods: It is an effective way to realize the goal of modernization of education in China by paying attention to the development and application of the reform of accounting teaching in Universities under the educational technology of big data. Results: This paper from the transformation of the university accounting education concept, in the era of big data under the background of accounting education in Colleges and universities how to give full play to the advantages of cloud computing, cloud platform construction of accounting education, then explore the reform of accounting education mode of. Conclusion: Therefore, this paper from the perspective of big data technology background, starting from the reform of the teaching mode of accounting and accounting industry background, considering the direction from the accounting personnel training, put forward the corresponding countermeasures for accounting teaching methods and teaching contents, promoting college accounting teaching reform.

scholarly journals The Construction and Thinking of Cloud Computing and Big Data Technology in Smart Campus

2019 ◽  
Vol 3 (2) ◽  
pp. 152
Author(s):  
Xianglan Wu
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Storage ◽  
Information Technologies ◽  
Rapid Development ◽  
Smart Campus ◽  
Huge Data ◽  
New Information ◽  
Big Data Technology

<p>In today's society, the rise of the Internet and rapid development make every day produce a huge amount of data. Therefore, the traditional data processing mode and data storage can not be fully analyzed and mined these data. More and more new information technologies (such as cloud computing, virtualization and big data, etc.) have emerged and been applied, the network has turned from informationization to intelligence, and campus construction has ushered in the stage of smart campus construction.The construction of intelligent campus refers to big data and cloud computing technology, which improves the informatization service quality of colleges and universities by integrating, storing and mining huge data.</p>

scholarly journals Big data technology in construction

2019 ◽  
Vol 97 ◽  
pp. 01032 ◽  
Author(s):  
Nikolay Garyaev ◽  
Venera Garyaeva
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Life Cycle ◽  
Construction Industry ◽  
Smart Cities ◽  
Entire Life ◽  
Entire Life Cycle ◽  
Intelligent Buildings ◽  
Big Data Technology

The article presents the results of the analysis of the use of large amounts of data in the construction industry, new trends such as BIM, IOT, cloud computing, intelligent buildings and smart cities with great prospects for application. These problems are related to the presence of huge amounts of data produced by the construction industry during the entire life cycle of a building, which are not fully used for optimizing processes and making decisions in construction.

Cloud Computing Model for Big Geological Data Processing

2013 ◽  
Vol 475-476 ◽  
pp. 306-311 ◽  
Author(s):  
Miao Miao Song ◽  
Zhe Li ◽  
Bin Zhou ◽  
Chao Ling Li
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Parallel Processing ◽  
Data Processing ◽  
Processing Unit ◽  
Geological Data ◽  
Computing Model ◽  
Operation Speed ◽  
Graphics Processing ◽  
Big Data Technology

Geological data with phyletic and various, huge and complex data format, the analysis of geological data processing is mainly divided into three parts: Mines forecast, mine evaluation and mine positioning. Traditional geological data analysis model is limited by limited storage space and computational efficiency, and cannot meet the needs of a large number of geological data fast operations. "Big data technology" provides the ideal solution to the vast amounts of geological data management, information extraction, and comprehensive analysis. For mass storage capacity and high-speed computing power that the "big data technology" need, we built an intelligence systems applied to the analysis of geological data based on MapReduce and GPU double parallel processing cloud computing model. For a large number of geological data, using hadoop cluster system to solve the problem of large amounts of data storage, and designing efficient parallel processing method based on GPU (Graphics Processing Units: calculation of Graphics Processing unit), the method was applied to MapReduce framework, finally completing MapReduce and GPU double parallel processing cloud computing model to improve the operation speed of the system. Through theoretical modeling and experimental verification, indicating that the system can meet the analysis of geological data operation precision, the operation data amount and the operation speed.

An Overview of Cloud Computing and Deployment of Big Data Analytics in the Cloud

2014 ◽  
pp. 209-215
Author(s):  
Pushpa Mannava
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analytics ◽  
Evaluation Method ◽  
Big Data Analytics ◽  
Modern Technology ◽  
Data Evaluation ◽  
Storage Space ◽  
Big Data Technology

Big Data is a data evaluation method makes it possible for by recent breakthroughs in details and interactions modern technology. However, big data evaluation requires a massive quantity of calculating resources making fostering costs of big data technology is not inexpensive for lots of small to tool business. In this paper, we detail the benefits as well as obstacles associated with deploying big data analytics through cloud computing. We suggest that cloud computer can support the storage space as well as computing requirements of big data analytics. This paper provides a detailed overview of cloud computing and deployment of big data analytics in the cloud.

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