基于云计算环境的大数据分析应用系统文献调研

发布时间：2019-07-09 12:00

【摘要】：在第二十一世纪,许多IT公司和组织决定采用的云计算与大数据技术。大数据已经成为IT领域一个非常重要的创新和成长点,例如云计算,物联网和数据分析的广泛应用。大数据分析(Big data analytics,简称BDA)可以帮助有关部门更好地理解信息中包含的数据,也有助于识别数据,最重要的是要发现数据中存在的价值。对于企业市场,有大量的例子证明了大数据分析的价值,如脸谱站,亚马逊河和谷歌等公司已经开始将大数据作为它们主要营销计划的一部分,以便更好地为客户服务。在分析数据时,BDA通常使用专门用于预测分析、应用数据挖掘、文本挖掘、预测和数据优化的软件工具,这就都需要云计算的技术支持。在过去的二十年中,云计算是一种高效的面向服务的计算平台。云计算和大数据之间的关系是云计算为大数据项目提供存储项目和计算平台。系统化文献调研(Systematic literature review,简称SLR)于2004年开始得到了软件工程研究人员的广泛关注。很多研究者报道了他们在软件工程中不同的研究领域应用系统化文献调研进行经验软件研究。软件工程从业者为了获得深入的了解,将系统性评价作为软件工程的一种新的研究方法。他们认为系统化文献调研是一种使用基于证据的知识体系的系统化文献综述方法。系统化文献调研作为一种系统化综述,被认为是基于证据的软件工程研究领域的一种关键研究方法学。系统化文献调研在得到广泛的关注之后,软件工程的研究者们在许许多多不同的研究当中使用了系统化文献调研,例如敏捷软件开发、回归测试、流程建模、可变性管理、成本估算等。研究者们也在发表的论文中总结归纳出了系统化文献调研的最佳实践方法以及他们使用系统化文献调研的经验。此外,系统化文献调研的技术策略评估以及质量报告也在研究中被提出。随着软件工程研究者们对系统化文献调研的兴趣的不断提高,系统化文献调研就必须提供适当的方法论指导其设计、执行和报告高质量的系统评价。本研究的目的是系统地研究现有的大数据以及云计算技术,总结了该技术的研究动向,主要介绍了大数据与云技术的相关技术和相关软件以及研究方法。为了进行调查和分析结果,本研究采用基于证据的软件工程范式的系统的审查方法。本论文提出了一个云技术与大数据分析的系统化文献调研(SLR)的研究文章。基于预定义的搜索策略,对717个文章进行了评估和鉴定,其中包括57个重要相关文献,选定的57篇文章发表在2010和2016年之间。论文定义了一个审查过程,通过制定审查协议,并提交审查的结果。本研究首先提出一个研究问题并通过对57篇文章的回顾和分析,试图回答这些问题,5W+1H分析法(what-什么事情,where-什么地点,when-什么时候,who-责任人,why-原因,how-如何)。研究结果将提供给研究人员,软件项目者和软件工程师关于现有的大数据分析云计算的现有方法的更多信息。我们正专注于如何将大数据和云计算纳入一个发展框架。此外,本文给出了关于云计算的大数据分析总结列表。本文发现,将大数据部署在云平台上面临一些有待解决的问题和挑战,例如数据安全和隐私保护等问题。虽然有一些研究者提出了部分应对方法,但本系统化文献调研发现这方面研究仍处于早期阶段,因此仍需要进一步进行深入研究。本文还给出了一系列的关于大数据和商务智能的论文清单,总结并给出了表格。
[Abstract]:In the twenty-first century, many IT companies and organizations decided to adopt cloud computing and big data technologies. Big data has become a very important innovation and growth point in IT, such as the wide application of cloud computing, Internet of Things and data analytics. Big data analytics (BDA) can help the department better understand the data contained in the information, and also help to identify the data, and the most important is to find the value that exists in the data. For the enterprise market, there are a large number of examples that demonstrate the value of big data analytics, such as Facebook, the Amazon and Google, have begun to use big data as part of their primary marketing plan to better serve customers. When analyzing data, BDA typically uses software tools that are dedicated to predictive analysis, application data mining, text mining, prediction, and data optimization, all of which require technical support for cloud computing. In the past two decades, cloud computing is an efficient service-oriented computing platform. The relationship between cloud computing and big data is the provision of storage and computing platforms for large data items by cloud computing. The systematic literature investigation (SLR) has been widely concerned by software engineering researchers in 2004. Many researchers have reported that they have applied systematic literature research in different fields of research in software engineering for empirical software research. In order to get an in-depth understanding, software engineering practitioners will make systematic evaluation as a new research method for software engineering. They believe that systematic literature investigation is a systematic literature review method using evidence-based knowledge system. As a systematic review, systematic literature research is considered to be a key research methodology in the field of evidence-based software engineering research. After extensive attention has been paid to systematic literature research, researchers in software engineering have used systematic literature research in many different studies, such as agile software development, regression testing, process modeling, variability management, cost estimation, and the like. The researchers also summarized the best practices for systematic literature research and their experience in the use of systematic literature research in published papers. In addition, the technical strategy assessment and quality report of systematic literature investigation are also put forward in the study. With the increasing interest of software engineering researchers in systematic literature research, systematic literature research must provide appropriate methodology to guide its design, implementation and reporting of high-quality system evaluation. The purpose of this study is to systematically study the existing big data and cloud computing technology, and summarize the research trend of the technology, mainly introduce the related technology and related software of the big data and cloud technology and the research method. In order to investigate and analyze the results, this study adopted the method of reviewing the system of the evidence-based software engineering paradigm. This paper presents a study on the systematic literature research (SLR) of cloud technology and big data analysis. Based on the predefined search strategy,717 articles were evaluated and identified, including 57 important relevant literature, and the selected 57 articles were published between 2010 and 2016. The paper defines a review process, through the development of a review agreement, and the results of the review. This study first presents a study and attempts to answer these questions through a review and analysis of the 57 articles, 5W + 1H analysis (what-what, where-where, when-when, when-responsible, why-why, how-how). The results of the study will be provided to the researchers, the software project, and the software engineer for more information about the existing methods of the existing big data analysis cloud computing. We are focusing on how to integrate big data and cloud computing into a development framework. In addition, this paper gives a summary of the big data analysis of cloud computing. It is found that the deployment of large data on the cloud platform is faced with some problems and challenges to be solved, such as data security and privacy protection. Although some of the investigators have proposed some methods of response, this systematic literature survey found that this study is still at an early stage and therefore requires further in-depth study. This paper also gives a series of paper lists of big data and business intelligence, and summarizes and gives a table.
【学位授予单位】：广西师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP311.13

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