Big data audit based on financial sharing service model

2020 ◽  
Vol 39 (6) ◽  
pp. 8997-9005
Author(s):  
Linghan Li ◽  
Yan Feng ◽  
Lei Li
Keyword(s):  
Big Data ◽  
Information Technologies ◽  
Enterprise Management ◽  
Service Model ◽  
Audit Process ◽  
Continuous Development ◽  
Other Information ◽  
Service Mode ◽  
The Government ◽  
Data Audit

As the COVID-19 epidemic continues to spread, the government has managed to prevent people from gathering. The audit work can only be carried out through the network, which puts forward higher requirements for the accuracy and effectiveness of the audit work. Under the background of the continuous development of big data and other information technologies, big data audit has gained important technical support and played an increasingly important role. Units at all levels gradually attach importance to the enterprise management mode based on the financial sharing service mode. This paper analyzes the related problems of big data audit under the financial sharing service mode, involving big data flow, big data preprocessing, big data audit process and other issues, in order to provide useful reference for the implementation of big data audit by using the financial sharing service mode under the influence of COVID-19.

Research on marketing management system based on independent ERP and business BI using fuzzy TOPSIS

2021 ◽  
pp. 1-9
Author(s):  
Zou Tao ◽  
Bai Si Jun ◽  
Rong Xi Bai
Keyword(s):  
Big Data ◽  
Management System ◽  
Information Technologies ◽  
Rapid Development ◽  
Fuzzy Topsis ◽  
Marketing Management ◽  
Enterprise Management ◽  
Business Law ◽  
Other Information ◽  
Market Opportunities

The rapid development of cloud computing, big data, AI, BI and other information technologies has accelerated the process of enterprise modernization and informatization. The combination of computer technology and management science promoted the formation of modern enterprise management technology. Especially in today’s era of big data, in the face of massive data, how to quickly and accurately find out the required information, analyze the memory relation of data, find out the inherent business law hidden under massive information, and provide an important reference for enterprises to make business decisions and seek for market opportunities. A methodology that exhibits fuzzy TOPSIS model has been incorporated in this study. Fuzzy weights and fuzzy judgment about the management systems have employed to estimate the scores of evaluation. In order to solve this problem, this paper integrates independent ERP and BI, and studies and develops a marketing management system by using advanced technologies such as data warehouse, online analysis and data mining; The system extracts useful data from ERP data sources, and analyzes the internal rules and statistical results that can be used to guide the enterprise’s actions, so as to effectively improve the enterprise’s competitiveness.

scholarly journals APPLICATION OF BIG DATA IN ENTERPRISE MANAGEMENT

2021 ◽  
Author(s):  
FENG GUO ◽  
HUI-LIN QIN
Keyword(s):  
Information Technology ◽  
Big Data ◽  
Rapid Development ◽  
Enterprise Management ◽  
Complex Data ◽  
Real Economy ◽  
Existing Problems ◽  
Other Information ◽  
Big Data Application ◽  
Deep Integration

With the continuous development of information technology, enterprises have gradually entered the era of big data. How to analyze the complex data and find out the useful information to promote the development of enterprises is becoming more and more important in the modernization of science and technology. This paper expounds the importance and existing problems of big data application in enterprise management, and briefly analyzes and discusses its application in enterprises and its future development direction and trend. With the rapid development of Internet of things, cloud computing and other information technology, the world ushered in the era of big data. It has become a trend to promote the deep integration of Internet, big data, artificial intelligence and real economy. Due to the rapid development of economy, the amount of data information generated in the process of consumption and production is very large. Under the traditional management mode, enterprises can not meet the needs of the current social and economic development. However, the application of big data technology in enterprises can achieve better analysis and Research on these data information, so as to provide reliable data basis for enterprises to carry out various business management decisions.

The Research of Wisdom Campus Construction and Development Based on Internet of Things

2014 ◽  
Vol 989-994 ◽  
pp. 5439-5443 ◽  
Author(s):  
Yi Peng Wang
Keyword(s):  
Internet Of Things ◽  
Information Technologies ◽  
Science And Technology ◽  
Colleges And Universities ◽  
Mobile Internet ◽  
Continuous Development ◽  
Digital Resources ◽  
Library Management ◽  
New Information ◽  
Other Information

With the continuous development of science and technology, new information technologies such as Internet of Things, Mobile Internet quickly get into various industries. The vast majority of colleges and universities are actively constructing wisdom campus based on Internet of Things to effectively integrate campus personnel identification, library management, campus id and other information, and to ensure digital resources integration and sharing. This article mainly aims at further exploration of the construction and development of wisdom campus based on the characteristics of Internet of Things.

scholarly journals Big Data Precision Marketing Approach under IoT Cloud Platform Information Mining

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Wang Li
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Storage ◽  
Telecommunications Industry ◽  
Cloud Platform ◽  
Service Model ◽  
Information Mining ◽  
Service Guarantee ◽  
Service Mode ◽  
Marketing Approach

In this article, an in-depth study and analysis of the precision marketing approach are carried out by building an IoT cloud platform and then using the technology of big data information mining. The cloud platform uses the MySQL database combined with the MongoDB database to store the cloud platform data to ensure the correct storage of data as well as to improve the access speed of data. The storage method of IoT temporal data is optimized, and the way of storing data in time slots is used to improve the efficiency of reading large amounts of data. For the scalability of the IoT data storage system, a MongoDB database clustering scheme is designed to ensure the scalability of data storage and disaster recovery capability. The relevant theories of big data marketing are reviewed and analyzed; secondly, based on the relevant theories, combined with the author’s work experience and relevant information, a comprehensive analysis and research on the current situation of big data marketing are conducted, focusing on its macro-, micro-, and industry environment. The service model combines the types of user needs, encapsulates the resources obtained by the alliance through data mining for service products, and publishes and delivers them in the form of data products. From the perspective of the development of the telecommunications industry, in terms of technology, the telecommunications industry has seen the development trend of mobile replacing fixed networks and triple play. The development of emerging technologies represented by the Internet of Things and cloud computing has also led to technological changes in the telecommunications industry. Operators are facing new development opportunities and challenges. It also divides the service mode into self-service and consulting service mode according to the different degrees of users’ cognition and understanding of the service, as well as proposes standardized data mining service guarantee from two aspects: after-sales service and operation supervision. A customized data mining service is a kind of data mining service for users’ personalized needs. And the intelligent data mining service guarantee is proposed from two aspects of multicase experience integration and group intelligence. In the empirical research part, the big data alliance in Big Data Industry Alliance, which provides data mining service as the main business, is selected as the research object, and the data mining service model of the big data alliance proposed in this article is applied to the actual alliance to verify the scientific and rationality of the data mining service model and improve the data mining service model management system.

Accounting Information System under the Digital Transformation

2021 ◽  
pp. 23-29
Author(s):  
Tamara Kucherenko ◽  
◽  
Halyna Anishchenko ◽  
Liudmyla Melnyk ◽  
Beata Anna Glinkowska-Krauze ◽  
...  
Keyword(s):  
Information System ◽  
Financial Reporting ◽  
Information Technologies ◽  
Accounting Information ◽  
Digital Transformation ◽  
Enterprise Management ◽  
Modern Theory ◽  
Accounting System ◽  
Accounting Information System ◽  
Other Information

Modern theory and accounting practice are formed under the influence of many factors, including economic integration, digitalization of communication and management processes, expansion of requirements for the information content of financial and non-financial reporting. In this regard, the purpose of the article is to disclose the structure of the accounting information system, the interdependence of its components, and determine the factors of its modernization in the context of the digital transformation of the socio-economic environment. The structure of the accounting information system was disclosed based on the identification of components that ensure the integration of the internal accounting systems of individual economic entities with the general accounting system. The modeling of the relationship of the components of the accounting information system with other information management systems of economic entities has been carried out. Information systems used to manage organizations were classified. It has been proven that an accounting information system is irreplaceable and plays a fundamental role in the management system. The improvement of information technologies determines the constant modernization of accounting and reporting, the formation of a qualitatively new accounting information environment (cloud accounting, blockchain, network accounting, etc.). Prospects for the further development of enterprise management are associated with the integration processes between the components of the accounting information system. Deepening the digitalization of accounting processes will expand the possibilities of analysis, planning, and forecasting at the management level of an enterprise, industry, and state economy.

Research on big data audit based on financial sharing service model using fuzzy AHP

2021 ◽  
pp. 1-10
Author(s):  
Sai Jiang
Keyword(s):  
Big Data ◽  
Fuzzy Ahp ◽  
Evaluation Model ◽  
Rapid Development ◽  
Implementation Process ◽  
Practical Significance ◽  
Service Model ◽  
Specific Content ◽  
Process Framework ◽  
Data Audit

With the rapid development of artificial intelligence and big data technology, the traditional audit method has been constantly impacted by big data. In the era of big data, enterprises actively explore and build a financial sharing service model, and through this model, build audit methods based on big data. In this paper, based on the financial sharing service model, we elaborate the preprocessing process of big data collection, clarity and storage, and build the simulation process framework of big data audit under the service model. Evaluation model is developed based on fuzzy analytic hierarchy process (AHP) and methodology for order estimation by similarity of solution. Finally, on the basis of the implementation process framework, the specific content of each link of big data audit is briefly given. Under the financial sharing service mode, it provides theoretical guidance and practical significance for the implementation of big data audit

scholarly journals A News Big Data Analysis of Issues in Higher Education in Korea amid the COVID-19 Pandemic

2021 ◽  
Vol 13 (13) ◽  
pp. 7347
Author(s):  
Jangwan Ko ◽  
Seungsu Paek ◽  
Seoyoon Park ◽  
Jiwoo Park
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Data Analysis ◽  
College Education ◽  
Big Data Analysis ◽  
Second Phase ◽  
Public Attention ◽  
Job Market ◽  
Media Reports ◽  
The Government

This paper examines the main issues regarding higher education in Korea—where college education experienced minimal interruptions—during the COVID-19 pandemic through a big data analysis of news articles. By analyzing policy responses from the government and colleges and examining prominent discourses on higher education, it provides a context for discussing the implications of COVID-19 on education policy and what the post-pandemic era would bring. To this end, we utilized BIgKinds, a big data research solution for news articles offered by the Korea Press Foundation, to select a total of 2636 media reports and conducted Topic Modelling based on LDA algorithms using NetMiner. The analyses are split into three distinct periods of COVID-19 spread in the country. Some notable topics from the first phase are remote class, tuition refund, returning Chinese international students, and normalization of college education. Preparations for the College Scholastic Ability Test (CSAT), contact and contactless classes, preparations for early admissions, and supporting job market candidates are extracted for the second phase. For the third phase, the extracted topics include CSAT and college-specific exams, quarantine on campus, social relations on campus, and support for job market candidates. The results confirmed widespread public attention to the relevant issues but also showed empirically that the measures taken by the government and college administrations to combat COVID-19 had limited visibility among media reports. It is important to note that timely and appropriate responses from the government and colleges have enabled continuation of higher education in some capacity during the pandemic. In addition to the media’s role in reporting issues of public interest, there is also a need for continued research and discussion on higher education amid COVID-19 to help effect actual results from various policy efforts.

scholarly journals DaLiF: a data lifecycle framework for data-driven governments

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Syed Iftikhar Hussain Shah ◽  
Vassilios Peristeras ◽  
Ioannis Magnisalis
Keyword(s):  
Big Data ◽  
Data Management ◽  
Good Governance ◽  
Business Community ◽  
Data Driven ◽  
Governmental Organizations ◽  
Data Lifecycle ◽  
The Government ◽  
Data Ecosystem ◽  
Governance Transparency

AbstractThe public sector, private firms, business community, and civil society are generating data that is high in volume, veracity, velocity and comes from a diversity of sources. This kind of data is known as big data. Public Administrations (PAs) pursue big data as “new oil” and implement data-centric policies to transform data into knowledge, to promote good governance, transparency, innovative digital services, and citizens’ engagement in public policy. From the above, the Government Big Data Ecosystem (GBDE) emerges. Managing big data throughout its lifecycle becomes a challenging task for governmental organizations. Despite the vast interest in this ecosystem, appropriate big data management is still a challenge. This study intends to fill the above-mentioned gap by proposing a data lifecycle framework for data-driven governments. Through a Systematic Literature Review, we identified and analysed 76 data lifecycles models to propose a data lifecycle framework for data-driven governments (DaliF). In this way, we contribute to the ongoing discussion around big data management, which attracts researchers’ and practitioners’ interest.

Big Data in the philippines: How do we actually use them?

2021 ◽  
pp. 1-30
Author(s):  
Lisa Grace S. Bersales ◽  
Josefina V. Almeda ◽  
Sabrina O. Romasoc ◽  
Marie Nadeen R. Martinez ◽  
Dannela Jann B. Galias
Keyword(s):  
Big Data ◽  
High Speed ◽  
The Philippines ◽  
Complex Data ◽  
Official Statistics ◽  
Group Discussions ◽  
The Public ◽  
The Government ◽  
The Many ◽  
Current Utilization

With the advancement of technology, digitalization, and the internet of things, large amounts of complex data are being produced daily. This vast quantity of various data produced at high speed is referred to as Big Data. The utilization of Big Data is being implemented with success in the private sector, yet the public sector seems to be falling behind despite the many potentials Big Data has already presented. In this regard, this paper explores ways in which the government can recognize the use of Big Data for official statistics. It begins by gathering and presenting Big Data-related initiatives and projects across the globe for various types and sources of Big Data implemented. Further, this paper discusses the opportunities, challenges, and risks associated with using Big Data, particularly in official statistics. This paper also aims to assess the current utilization of Big Data in the country through focus group discussions and key informant interviews. Based on desk review, discussions, and interviews, the paper then concludes with a proposed framework that provides ways in which Big Data may be utilized by the government to augment official statistics.

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