In your study and work, you will always come into contact with papers. There are many types of papers, including academic year papers, graduation papers, dissertations, scientific papers, achievement papers and so on. In order to make it easier and more convenient for you to write papers, the following papers are carefully arranged by me based on the opportunities and challenges in the era of big data, which are for reference only and I hope to help you.
Opportunities and challenges based on the era of big data
1, Overview of Big Data Foundation
Big data refers to data that exceeds the processing capacity of traditional database systems. It has the following four basic characteristics, namely, mass, diversity, variability and high speed. At the same time, various data types, relatively low data value density, fast processing speed and high timeliness requirements are also its main characteristics.
2. The impact of big data in the times
Big data has a profound impact on economy, politics, culture and other aspects. It can help people to carry out quantitative management, which is more scientific and targeted, and those who get data win the world. The impact of big data on the times mainly includes the following aspects:
(1) "big data decision-making" is more scientific and effective. If people make decisions based on big data analysis, they can fully obtain relevant decision-making information and let data dominate decision-making. This method will certainly promote the innovation and reform of decision-making methods, completely change the traditional decision-making methods, improve the scientific nature of decision-making, and promote the repositioning of information management standards. The outbreak of influenza A (H 1N 1) in 2009 is a successful example of using big data. Google judges the spread source of influenza by analyzing a large number of records searched on the Internet, and officials of public health institutions take targeted action decisions through these valuable data information.
(2) "Big Data Application" promotes industry integration. Although big data originated in the communication industry, its influence is not limited to the communication industry, and it will inevitably have a far-reaching impact on others. At present, big data is gradually being widely used in various industries and fields, and more and more enterprises begin to strengthen daily management and operation management with data analysis as an auxiliary means. For example, the location of flagship stores such as McDonald's, KFC and Apple is based on big data analysis, and data analysis technology is also widely used in the retail industry.
(3) "Big data development" promotes technological change. The application demand of big data is the source of the development of new technologies of big data. It is believed that with the continuous development of the times, the data analysis and data mining functions of computer systems will gradually replace the previous field applications that rely solely on people's own judgment. With these innovative big data applications, the energy of data will be amplified layer by layer.
In addition, it should be noted that big data is easy to cause some privacy leaks in terms of personal privacy. We need to take this problem seriously, comprehensively use legal, propaganda and moral means, and make more active efforts to protect personal privacy.
3. Coping strategies for big data
3. 1 R&D and innovation of key technologies for layout.
At present, the technical threshold of big data is relatively high, and most of them are information technology enterprises with advantages in data storage and analysis. To promote industrial upgrading, we must strengthen research and attach importance to the research and development and application of key technologies and emerging technologies for data analysis, specifically from the following aspects: First, lay a solid foundation for development, take the core technology of big data as the starting point, strengthen theoretical research and technology research and development in the fields of artificial intelligence, machine learning and business intelligence, and lay a theoretical foundation for the application of big data. The second is to speed up the research and development of basic technologies (unstructured data processing technology, visualization technology, non-relational database management technology, etc.). ), and organically integrated with technologies such as Internet of Things, mobile Internet and cloud computing, laying a solid foundation for the formulation of solutions. Third, based on the application of big data, focus on the research and development of core technologies such as knowledge computing (search) technology, knowledge base technology and web search technology, strengthen the research and development of individual technology products, ensure the quality improvement, and promote the organic combination of them with data processing technology to establish a scientific and technological system.
3.2 Improve the development level of software products.
First, promote Industry-University-Research cooperation with enterprises as the main body and improve the level of software development. The second is to use cloud computing technology to promote the transformation and development of information technology service industry and promote the construction of Chinese knowledge base, database and rule base. Third, encourage software and hardware enterprises and service enterprises to apply new technologies to provide data information services and provide system integration solutions with industry characteristics. Fourth, large Internet companies take the lead in gathering small and medium-sized Internet information service providers, systematically integrating superior resources, and developing and integrating localized information services. Fifth, data processing software vendors should take the lead. These software vendors must have certain basic advantages. Can give full play to their respective data advantages and technical advantages, complementary advantages, improve the development level of data software, improve the accuracy and scientificity of service content. At the same time, improve the market ability and integration level of big data solution providers to ensure that their big data provides mature solutions for various industries.
3.3 Accelerate the demonstration application of big data.
In the era of big data, we should actively promote the demonstration application of big data, which can be practiced from the following aspects: First, for some fields with large data (such as finance, energy, circulation, telecommunications, medical care, etc.), we should guide industry manufacturers to actively participate and vigorously develop industrial application solutions integrating software and hardware, such as data monitoring and analysis, horizontal expansion storage, and business decision-making. Second, big data will be gradually applied to smart city construction and personal life services to improve the development level of services such as digital content processing software. Thirdly, to promote the in-depth development of industry databases (especially in high-tech fields), it is suggested to establish different thematic databases for different industry fields, provide corresponding content value-added services and form characteristic services. Fourth, take key areas or key enterprises as a breakthrough, analyze, sort out and clean up the enterprise data accordingly, and gradually reduce and eliminate duplicate data and noise data.
3.4 Optimize and improve the development environment of big data.
Information security is the main problem in the application of big data. Therefore, we should strengthen the research on information security based on big data information collection and analysis, formulate effective preventive measures and strengthen information security management. At the same time, in order to optimize and improve the development environment of big data, we should adopt various incentive policies (such as including the data processing business of enterprises with certain capabilities in the scope of preferential business tax policies) to support the development of data processing enterprises and promote them to improve the level and quality of data analysis and processing services. The third is to consolidate the application foundation of big data, improve relevant institutional mechanisms, and promote the centralized sharing of information resources with the government as the starting point.
To achieve the above points, when the era of big data comes, we will not be helpless in the face of a large amount of data, but will bear in mind that the benefits obtained from data will also promote the rapid development of the country and enterprises.
Big data provides favorable conditions for horizontal cross-border operation, cross-border integration of industries and integration of production and consumption. Big data will definitely have a great impact on people's lives in social economy, politics and culture, and the era of big data also poses new challenges and opportunities for human data control. In the face of new challenges and development opportunities, we should actively respond to them in order to grasp the initiative of big data development in the future.
structure
A paper usually consists of name, author, abstract, keywords, text, references and appendices, some of which (such as appendices) are optional.
1, paper title
Requirements are accurate, concise, eye-catching and novel.
2. Contents
A table of contents is a brief table of the main paragraphs in a paper. (Essays don't need to be listed in the table of contents)
3. Platform for Action
It is an excerpt from the main content of the article, which requires short and concise content.
4, keyword definition
Keywords are selected from the title, abstract and text of the paper, which are words with substantial meaning to express the central content of the paper. Keywords are words used by computer systems to index the content characteristics of papers, which are convenient for information systems to collect and provide readers with retrieval. Generally, 3-8 words are selected as keywords for each paper, and a new line is set at the bottom left of the "abstract".
Subject words are standard words. When determining the subject words, we should analyze the theme of the paper and convert it into standard words in the thesaurus according to the rules of indexing and collocation. (See Chinese Thesaurus and World Chinese Thesaurus).
5. The text of the paper
(1) Introduction: Introduction, also known as preface, preface and introduction, is used at the beginning of the paper. The introduction generally outlines the author's intention, explains the purpose and significance of the topic, and points out the writing scope of the paper. The introduction should be short and concise, and stick to the theme.
(2) Text of the paper: The text is the main body of the paper and should include arguments, arguments, argumentation process and conclusions. The main part includes the following contents:
A. Questions-arguments;
B. analyzing the problem-arguments and arguments;
C. problem solving-demonstrating methods and steps;
D. conclusion.
Step 6 refer to
Thesis references are the main documents that can be referenced or cited in research and writing, and are listed at the end of the paper. Reference materials should be marked on new pages according to.
7. Paper binding
All relevant parts of the paper were copied out. After inspection, there is no problem. Put it in the book and add a cover. The cover of the paper should be concise and generous, and the title, school, department, instructor's name, author's name and completion date should be written. The author's name of the thesis topic must be written on the surface, not on the supplementary page inside.
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