Research on Big Data Risk Control Model of Venture Capital

2021 ◽  
Author(s):  
Boao Cui
Keyword(s):  
Big Data ◽  
Venture Capital ◽  
Risk Control ◽  
Control Model

Risk Control Study Based on the Digital Recording Technology Industry Investment Projects in "Internet +"

2020 ◽  
Vol 14 ◽  
Author(s):  
Yan Zhou
Keyword(s):  
Venture Capital ◽  
Digital Technology ◽  
Risk Control ◽  
Investment Risk ◽  
Digital Recording ◽  
Project Investment ◽  
Recording Technology ◽  
Technology Project ◽  
Investment Evaluation ◽  
Risk Investment

Background: The reform and innovation of recording technology has resulted in recording becoming an exciting, developing project. Against the background of Internet +, traditional analogue technology has developed into digital recording technology, playing an important role in various fields. Venture capital in digital recording technology projects has also attracted attention from all circles. Objective: This paper aims to, by sorting out literature on venture capital, analyze the measurement method of project investment risk, and then, after analyzing the risk factors existing in the investment of digital recording technology under the “Internet +”, propose measures to control these risk factors. At the same time, taking CY company as an example, the investment risk prevention strategy of digital recording technology project is applied to the risk investment evaluation practice of CY company. Methods: This paper reviews and comments the literature on venture capital, and sorts out the evaluation methods of project investment risk. After studying the project investment risk of digital recording technology, this paper finds out the preventive strategies to deal with these risks, and applies them to risk investment evaluation of CY. This paper proposes investment suggestions basing on various factors, and makes an overall evaluation of the value of digital recording technology project, which hopefully will act as a reference for venture capital institutions when investing in digital recording technology in the future. Results: The countermeasures against investment risks in digital recording technology projects are: 1. Identification of countermeasures against investment risks in digital recording technology projects. 2. Encouragement and promotion of joint-stock cooperation and reduction of operational risks 3. Establishment and improvement of financial risk control. Conclusion: Digital technology, which is continuously improving, has penetrated recording technology. With mindful awareness of investment risks and careful investment in recording technology projects, digital technology can improve living standards while making the flexibility and form of recording work more artistic and enabling recording technology to reach new heights.

A watermark-based in situ access-control model for image big data

2019 ◽  
pp. 67-87
Author(s):  
Liangli Ma ◽  
Jinyi Guo ◽  
Wei Ren ◽  
Vi Ren ◽  
Lizhe Wang ◽  
...  
Keyword(s):  
Big Data ◽  
Access Control ◽  
Control Model ◽  
Access Control Model

scholarly journals Influence of Venture Capital and Knowledge Transfer on Innovation Performance in the Big Data Environment

2019 ◽  
Vol 12 (4) ◽  
pp. 188 ◽  
Author(s):  
Chuanrong Wu ◽  
Xiaoming Yang ◽  
Veronika Lee ◽  
Mark E. McMurtrey
Keyword(s):  
Big Data ◽  
Knowledge Transfer ◽  
Venture Capital ◽  
New Product ◽  
User Preferences ◽  
Innovation Performance ◽  
Venture Capitalists ◽  
New Knowledge ◽  
Data Environment ◽  
Start Ups

Technological innovation requires large investments. Venture capital (VC) is a prominent financial source for innovative start-ups. A venture capitalist will inevitably transfer knowledge to facilitate the innovation of a firm while monitoring and advising its portfolio companies. Only when a firm has its own valuable new knowledge and high growth potential would venture capitalists select it. At the same time, big data knowledge, such as customer demands and user preferences, is also important for the new product development of a firm in the big data environment. Therefore, private knowledge transferred from venture capitalists, new knowledge developed independently by a firm itself, and big data knowledge are the three main types of knowledge for venture-backed firms in the big data environment. To find the influences of VC and knowledge transfer on the innovative performance of venture-backed firms, a model of maximizing the present value of the expected profit of new product innovation performance of a venture-backed firm in the big data environment is presented. The model can help venture capitalists to determine the scale of investment and the optimal exit time and predict the internal rate of return (IRR). This model can also help innovative start-ups to illustrate the value and prospects of a project to attract investment in their business prospectus.

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