Big Data Killing: Price Discrimination in Algorithmic Economy

the rapid development of Internet technology makes our real life more and more dependent on big data technology. English is one of the most widely spoken and popular languages in the world. At present, the cultivation of English majors in China needs appropriate reform. Curriculum reform should be carried out against the background of big data, English teaching should be combined with the development of The Times, curriculum needs should be innovated, and teaching mode should be created to match the current economic development. Therefore, it is very important to explore the reform of English major courses under the background of big data. This paper firstly discusses the significance of the reform of the teaching mode of English majors under the background of big data, then discusses the influence of the reform on the teaching mode of English majors under the background of big data, and finally discusses the reform direction of the teaching mode of English majors under the background of big data.

The internet financial model is booming in the era of big data, and gradually penetrates into all aspects of people's lives. With the continuous development of network technology, under the background of big data, people's living standards are constantly improving, and higher requirements are put forward for the quality of life. In order to promote the sustainable development of the internet finance industry, seize the opportunity and strengthen itself in the era of big data, the internet finance industry needs to uphold the development concept of pluralism and openness. Internet finance has played a positive role in improving the efficiency of financial services and formed a new payment method. With the help of big data, internet finance is constantly innovating Internet financial products, while some risks are amplified under the background of financial big data. On the basis of expounding the concepts of big data and Internet financial risks, this paper provides a method for the construction of Internet financial risk control model based on data envelopment analysis and the main forms of Internet financial risks.

In the era of big data, cloud computing and big accounting data are combined to build a cloud accounting application platform that mainly integrates spatial distribution, security, accessibility, and the importance of transforming the state of accounting information. In the face of the wave of economic development, cloud accounting will also begin to be applied to administrative agencies and show great vitality in these departments. On this basis, this article focuses on the application of cloud accounting in government accounting under the background of big data. This article attempts to analyze the characteristics of cloud accounting to explore its functions and application services. In the new requirements of the new government accounting system, the importance of “big data” in the implementation of the new government accounting system is systematically analyzed. The use of cloud accounting in the government compares the settings and levels of the application with traditional government accounting work. The research results show that the emergence of cloud accounting is a major change in the accounting industry. It improves production efficiency and reduces company costs, and is favored by units. But cloud computing has some disadvantages. In today’s digital age, how to make cloud accounting a foothold takes a long time to think about how to make cloud accounting seize opportunities and respond to challenges.

Research on the impact of supply chain digital transformation on enterprise competitiveness based on big data background

In the era of the construction engineering industry informatization, the collection, storage, and reuse of big construction data is the only way to apply and inform big data in the construction industry. Relying on the reverse logistics management system, modern construction technology can simulate the timeliness of materials, funds, and time limits of the actual construction site according to the logistics reverse engineering principle. Then, reverse the active management status of the internal logistics model of the actual project. It is one of the critical problems for construction engineering informatization to study applying big data and cloud computing technology to solve problems from massive and complicated data or mass data. Since the research on big data and cloud computing technology started late in construction engineering, it is worth studying which aspects of these technologies can be used in the whole life cycle of this field. This paper proposes a structural construction optimization identification method based on IPEM rapid reanalysis. USES the co-solubility of reverse logistics structure construction technology and applied the data mining method to solve many problems such as refined construction management leftover material surplus in the later construction stage. Finally, a construction optimization model of reverse logistics building system based on improved data mining is proposed according to the actual engineering requirements.

Amazon Exclusive: Q&A with Kenneth Cukier and Viktor Mayer-Schonberger Q. What did it take to write Big Data? A. Kenn has written about technology and business from Europe, Asia, and the US for The Economist, and is well-connected to the data community. Viktor had researched the information economy as a professor at Harvard and now at Oxford, and his book Delete had been well received. So we thought we had a good basis to make a contribution in the area. As we wrote the book, we had to dig deep to find unheard stories about big data pioneers and interview them. We wanted Big Data to be about a big idea, but also to be full of examples and success stories -- and be engrossing to read. Q. Are you big datas cheerleaders? A. Absolutely not. We are the messengers of big data, not its evangelists. The big data age is happening, and in the book we take a look at the drivers, and big datas likely trajectory: how it will change how we work and live. We emphasize that the fundamental shift is not in the machines that calculate data, but in the data itself and how we use it. Q. In discovering big data applications, what was your biggest surprise? A. It is tempting to say that it was predicting exploding manholes, tracking inflation in real time, or how big data saves the lives of premature babies. But the biggest surprise for us perhaps was the very diversity of the uses of big data, and how it already is changing peoples everyday world. Many people see big data through the lens of the Internet economy, since Google and Facebook have so much data. But that misses the point: big data is everywhere. Q. Is Big Data then primarily a story about economic efficiency? A. Big data improves economic efficiency, but thats only a very small part of the story. We realized when talking to dozens and dozens of big data pioneers that it improves health care, advances better education, and helps predict societal changefrom urban sprawl to the spread of the flu. Big data is roaring through all sectors of the economy and all areas of life. Q. So big data offers only upside? A. Not at all. We are very concerned about what we call in our book the dark side of big data. However the real challenge is that the problem is not necessarily where we initially tend to think it is, such as surveillance and privacy. After looking into the potential misuses of big data, we became much more troubled by propensity -- that is, big data predictions being used to police and punish. And by the fetishization of data that may occur, whereby organizations may blindly defer to what the data says without understanding its limitations. Q. What can we do about this dark side? A. Knowing about it is the first step. We thought hard to suggest concrete steps that can be taken to minimize and mitigate big datas risk, and came up with a few ways to ensure transparency, guarantee human free will, and strike a better balance on privacy and the use of personal information. These are deeply serious issues. If we do not take action soon, it might be too late.

With the rapid development of Internet technology, digital media art design has become a new research hotspot. In this era of information explosion, huge data and endless knowledge, people have more and more unusual and unique profound influences on big data technology and digital advertising creativity. Digital media art design is a new creative concept, and the shadow of digital media is constantly emerging in modern advertising. Based on the development of modern advertising, this article studies the application of its digital media art in the context of big data. This article mainly uses observation method, case analysis method, questionnaire survey method and other methods for research. The results of the questionnaire survey show that the application of digital media art design in modern advertising is a general trend. In addition, since 30% of people pursue visual effects, the design of advertisements should also be more visually designed.KeywordsBig dataDigital mediaArt designModern advertising

With the rapid development of cloud computing and mobile Internet technology, huge amounts of data are generated on the network at every moment. In the era of big data, most of the data are designed in distributed storage, stored on many independent sites. The typical data mining algorithm can not meet the requirement of privacy data security in the big data background. In the big data background, distributed data mining is faced with the need to solve data security, privacy disclosure and other technical problems. Therefore, this paper applies homomorphic encryption technology to typical K-means clustering mining algorithm, and designs a distributed privacy protection PP-kmeans algorithm based on big data. Experiments show that this algorithm can realize data privacy security protection. And more accurate big data clustering mining effect is achieved.

With the deepening of economic and financial globalization and integration, many economic and financial departments need a large number of high-quality application-oriented professionals who are familiar with financial theory and financial practice. Under the background of big data, the universality and comprehensiveness, theoretical and practical, epochal and forward-looking of financial professional courses are increasingly prominent. These characteristics need rich data, charts to illustrate and demonstrate, must rely on the network and big data platform, in order to achieve good teaching effect. Therefore, in order to achieve the expected teaching objectives, teaching methods must be reformed and various teaching methods and forms should be adopted flexibly in the teaching process of finance major.

Aiming at the problem of effective management of a large number of teaching data resources, this paper puts forward an optimization method of student management evaluation system under the background of big data. Firstly, the model of student education management is constructed with big data technology, and the evaluation index of student management is standardized. Secondly, improve the student management evaluation algorithm, and optimize the student management evaluation system. Finally, the experiment proves that the optimization method of student management evaluation system under the background of big data has high practicability and fully meets the research requirements.

The incidence of children with autism is high and attracts the attention of researchers worldwide. Big data technology is the main driving force for children's rehabilitation, which will greatly promote the development of children's rehabilitation industry. Using big data to children's rehabilitation can meet the needs of integrating and sharing children's rehabilitation information resources, optimize the rehabilitation process, and promote the coordinated development of children's rehabilitation. This article, mainly from the relevant children treatment and intervention, combined with recent research hot point —fusion rehabilitation, summarized and comprehensively analyzed the status of the research related to children with autism under the background of big data, which aims to promote children with autism and families actively participate in and shape their life, promote the integration of society. It is necessary to provide enlightenment for the subsequent relevant rehabilitation institutions or hospitals to further carry out children's rehabilitation.

Cloud Accounting is an online accounting information system based on computing and customer use the computer or other devices to achieve accounting and financial analysis functions. The development and popularization of cloud computing may have a great impact on corporate accounting information application and building model, which will provide favorable conditions for the development of SMEs. Based on the author's work and learning experiences, this paper first analyzed the accounting data processing issues under the background of big data, Then, on this basis, the paper proposed the model building strategy under the background of big data, where the author made a profound analysis for the model, Finally, the article proposed the accounting application countermeasures in the big data background.

With the improvement of the level of market economy and the improvement of the state's attention to small and medium-sized enterprises (SME), the number of small and medium-sized enterprises in China is gradually increasing, and the market competition is also becoming increasingly fierce. Under the background of big data, the competition faced by small and medium-sized enterprises is more severe. Strengthening the management of financial internal control can ensure that enterprises can successfully complete their development goals and improve their market competitiveness, so as to realize the healthy development of small and medium-sized enterprises. Combined with the significance of financial internal control of small and medium-sized enterprises under the background of big data, this paper emphatically analyzes the problems existing in financial internal control of small and medium-sized enterprises under the background of big data. According to the analysis results, this paper puts forward the strategies of financial internal control of small and medium-sized enterprises under the background of big data, for reference.

As a kind of new information technology, big data is developing rapidly. It plays an important role in people's daily production and life. However, as the big data is related to people's production and life, a series of privacy security issues have gradually emerged. Based on the background of the current big data era, this paper analyses and discusses the basic theory of big data and privacy, and analyzes and studies the possible privacy security problems under the background of big data, finds out the root causes of the problems, and puts forward corresponding countermeasures. The author hopes that through this study and reflection, it can give some reference to scholars who study big data, and also let people know how to protect their personal privacy in the context of Big Data.

With the advent of the cloud era, big data has attracted more and more attention. At present, due to the expansion of the scale of chain educational training institutions and the complexity of management, the information stored in the data of management platform is mostly unstructured data model. The large amount and complexity of unstructured data become the main difficulties in big data analysis and decision-making. This paper analyzes and discusses the application of chain educational training institutions based on the background of big data, and build a platform for big data analysis and decision-making of chain educational training institutions based on cloud computing. The platform greatly improves the ability to process massive data and discovers the internal relationship and rules between big data. It aims to make better use of big data to serve chain educational training institutions, promote the continuous development and progress of chain educational training institutions, and even lay the foundation for the global chain educational training institutions.