The Influence of Social Media on College Choice among Undergraduates Majoring in Big Data Management and Application in China:Taking Guilin University of Electronic Technology as an Example

This study aims to investigate the influence of social media on college choice among undergraduates majoring in Big Data Management and Application in China.The study attempts to reveal how information on social media platforms such as Weibo,WeChat,and Zhihu influences the cognition and choice process of prospective students.By employing an online quantitative survey questionnaire,data were collected from the 2022 and 2023 classes of new students majoring in Big Data Management and Application at Guilin University of Electronic Technology.The aim was to evaluate the role of social media in their college choice process and understand the features and information that most attract prospective students.Social media has become a key factor influencing the college choice decision-making of undergraduates majoring in Big Data Management and Application in China.Students tend to obtain school information through social media platforms and use this information as an important reference in their decision-making process.Higher education institutions should strengthen their social media information dissemination,providing accurate,timely,and attractive information.It is also necessary to ensure effective management of social media platforms,maintain a positive reputation for the school on social media,and increase the interest and trust of prospective students.Simultaneously,educational decision-makers should consider incorporating social media analysis into their recruitment strategies to better attract new student enrollment.This study provides a new perspective for understanding higher education choice behavior in the digital age,particularly by revealing the importance of social media in the educational decision-making process.This has important practical and theoretical implications for higher education institutions,policymakers,and social media platform operators.

Research on the Application of Big Data and Cloud Computing Technology in Smart Campus

The current education field is experiencing an innovation driven by big data and cloud technologies,and these advanced technologies play a central role in the construction of smart campuses.Big data technology has a wide range of applications in student learning behavior analysis,teaching resource management,campus safety monitoring,and decision support,which improves the quality of education and management efficiency.Cloud computing technology supports the integration,distribution,and optimal use of educational resources through cloud resource sharing,virtual classrooms,intelligent campus management systems,and Infrastructure-as-a-Service(IaaS)models,which reduce costs and increase flexibility.This paper comprehensively discusses the practical application of big data and cloud computing technologies in smart campuses,showing how these technologies can contribute to the development of smart campuses,and laying the foundation for the future innovation of education models.

Exploration and Practice of Big Data Introductory Courses for Big Data Management and Application Majors

As an introductory course for the emerging major of big data management and application,“Introduction to Big Data”has not yet formed a curriculum standard and implementation plan that is widely accepted and used by everyone.To this end,we discuss some of our explorations and attempts in the construction and teaching process of big data courses for the major of big data management and application from the perspective of course planning,course implementation,and course summary.After interviews with students and feedback from questionnaires,students are highly satisfied with some of the teaching measures and programs currently adopted.

Research on the Application of Big Data in Logistics Management

With the high-speed development of China’s information technology,human society has ushered in the age of big data,imposing challenges to many logistics companies.With the continuous changes in the development environment,it requires relevant logistics companies to make reasonable self-adjustment to ensure their adaptability to the development environment.At present,many Chinese logistics companies with relatively lagged management model fail to effectively employ big data analysis technique,and have some shortcomings in talent team construction.Therefore,relevant logistics companies need to reasonably use big data technology,improve the quality of logistics management work,and effectively screen valuable part from mass information,thereby promoting rapid development of China’s logistics industry.In this paper,the application of big data in logistics management is analyzed.Firstly,the concepts and characteristics of big data are introduced and then this paper discusses the necessity of application of big data in logistics management,and proposes specific application countermeasures,in hope of providing some reference to relevant staff.

Research on the Application of Big Data and Artificial Intelligence Technology in Computer Network

With the continuous development of social economy,science and technology are also in continuous progress,relying on the Internet technology of big data era has come in an all-round way.On the basis of the development of cloud computing and Internet technology,artificial intelligence technology has emerged as the times require.It also has more advantages.Applying it to computer network technology can effectively improve the data processing efficiency and quality of computer network technology,and improve the convenience for people’s life and production.This paper studies and analyzes the practical application requirements of computer network,and discusses the application characteristics and timeliness of artificial intelligence technology.

Research and Application Progress of Agricultural Big Data Technology and Resources

With the development of Internet of things, cloud computing, mobile Inter- net, the scale of the data shows an alarming growth trend. Agricultural information is an important part of modern agricultural construction, and the development of a- gricultural industry is becoming more and more deeply with the application of infor- mation technology. This paper reviewed the concept and characteristic of big data, development history of big data at home and abroad, and emphatically expounded the connotation of agricultural big data, development status of agricultural big data at home and abroad, as well as the applications of agricultural big data technology, agriculture big data resources and agricultural big data in various fields.

Improving Performance of Cloud Computing and Big Data Technologies and Applications

Cloud computing technology is changing the development and usage patterns of IT infrastructure and applications. Virtualized and distributed systems as well as unified management and scheduling has greatly im proved computing and storage. Management has become easier, andOAM costs have been significantly reduced. Cloud desktop technology is develop ing rapidly. With this technology, users can flexibly and dynamically use virtual ma chine resources, companies＇ efficiency of using and allocating resources is greatly improved, and information security is ensured. In most existing virtual cloud desk top solutions, computing and storage are bound together, and data is stored as im age files. This limits the flexibility and expandability of systems and is insufficient for meetinz customers＇ requirements in different scenarios.

我国“数字煤炭”建设发展研究与探讨

“数字煤炭”的内涵是通过数字技术与煤炭工业的深度融合,优化煤炭生产、运营、流通、转化、服务等各环节,全面推进煤炭工业及所关联对象的数字化进程,进而实现煤炭工业以安全、高效、绿色、智能、健康为核心目标的高质量发展。全面阐述了优化升级煤炭数字基础设施、全面赋能现代化煤炭产业体系、完善煤炭数字技术创新体系等10个方面“数字煤炭”建设的主要内容;为进一步提升“数字煤炭”建设水平,研究提出应突出顶层设计、健全体制机制、保障资金投入、实施示范评价等具体建议;认为在数字中国建设背景下,为实现煤炭工业高质量发展,“数字煤炭”建设势在必行。

大数据时代的农业发展:国际前沿与中国实践

随着信息革命、数据革命的到来,农业生产已经发生了翻天覆地的变化。在新时代,传统农业逐步遇到瓶颈,亟待向着精准农业、智慧农业等新型数字农业发展模式转型。21世纪以来,世界多国探索了农业大数据的十余个领域,发展了一系列数据收集、存储、分析的技术和方法,并取得了显著的应用成效。中国面临着人口多、耕地少等一系列问题,应紧跟技术进步,结合中国国情和农业特征,加快发展农业新质生产力,在农业大数据的基础研究、行业标准、基础设施、供应链管理、金融保险等方面着力,促进农业高质量发展,加快建设农业强国,促进农业农村现代化。

我国遗产型景区“平台(platform)+数据(data)+标准(standard)”管服体系构建初探

探索构建我国遗产型景区“平台(platform)+数据(data)+标准(standard)”管服体系是深入贯彻落实习近平新时代中国特色社会主义思想和党的二十大精神,推进科技治理体系和遗产型景区管理能力现代化发展的重要实践。随着文化旅游产业蓬勃发展,针对国家和地方遗产型景区管理现状,构建符合我国遗产型景区科技创新规律、适应遗产型景区新需求的科技创新管理体系,成为国家、省、市、区县中各类遗产型景区优化管理资源的重要途径。本文通过论述大数据、云计算、人工智能等相关技术,设计“横向到边、纵向到底”的总体建设思路,旨在构建统一标准、信息统筹、资源共享、监测预警、管理优化、决策支持等功能于一体的系统运行体系,为政府推动遗产型景区管理创新制定有效措施提出建议。

基于大数据技术的企业信息资源管理系统

企业信息资源管理系统面对大规模和多类型数据涌入时,处理效率低,系统容易崩溃,设计基于大数据技术的企业信息资源管理系统。分析Hadoop平台体系结构,确定资源管理系统整体架构,设计每个子系统对应的功能,部署系统硬件环境;利用大数据融合技术设置软件执行算法,通过模糊调度挖掘资源间关联规则,根据相似性函数,建立同类资源的融合模型,提高业务处理效率,完成系统整体设计。实验表明,该系统的CPU利用率仅在30%左右,处理时间在1.00s以内,大大缩短了处理时间,提高了处理效率。

大数据视域下区块链技术在数据溯源中的应用探究

随着大数据时代的到来,数据的采集、存储和处理变得更加便捷和高效,区块链技术作为一种去中心化的分布式账本技术,具有不可篡改、可追溯和去中心化的特点,为数据溯源提供了新的解决方案。文章介绍了大数据和区块链技术的基本概念,阐述了大数据视域下区块链技术在数据溯源中的应用流程,包括数据采集、存储、查询、统计和溯源,构建了大数据视域下区块链技术在数据溯源中的应用模型,研究其在不同领域的具体应用,以供参考。

数智技术时代的中国档案学学科发展

数智技术,直接导致我国千行百业的原始数据形成,其管理正发生前所未有的变化。为适应从人人相连走向万物智联的大数据安全管理,需要对我国高等教育相关学科专业进行系统研究。梳理数字技术对我国组织的业务活动及其原始记录形成和管理的作用影响之后,提出传统的“中国档案学”学科将演进为“档案大数据工程”学科。并且指出,档案大数据工程学科高等教育包括“管理文秘”“数据资源管理”“大数据技术”等专业,尝试提出以上几个专业建设的发展方向。

Applications and Challenges of Smart Technologies in Supply Chain Management

The advent of intelligent technologies in supply chain management(SCM)through the use of artificial intelligence(AI),the Internet of Things(IoT),blockchain,big data analytics,and others is a game changer.These improvements increase clarity,effectiveness,and flexibility,allowing companies to quickly deal with market changes and interruptions.Nevertheless,adopting such technologies comes with difficulties,such as information security,compatibility,exorbitant prices,and employee opposition.The applications of intelligent technologies for SCM are examined in this article,as well as the importance of their implementation and solutions that provide a competitive advantage for businesses.

大数据应用技术课程本研一体化教学体系建设

大数据应用技术课程对于数据科学的研究和发展、数据科学学科的建设、培育新型数据人才具有重要意义。本研一体化教学有助于提高本研学生的学习效率和创新能力,增强课程体系的延续性和实践性,重视学科交叉融合发展。从教学大纲修订、教学管理模式改革、教学评价方式三个方面探讨本研一体化教学体系建设的重点问题,全面阐述大数据应用技术课程本研一体化教学改革的路径选择和实践,致力于培养学生长期内驱力和创新能力,为国家和社会发展培育高质量数据人才。

大数据时代智慧农业实验室管理创新策略研究

大数据时代背景下,高校智慧农业实验室作为农业教育与科研的关键平台,面临管理革新需求。当前,这些实验室普遍采用的传统管理系统与智慧农业的快速发展不相匹配,限制了其潜能发挥。本文针对性地分析了智慧农业实验室的管理现状,并依托大数据技术,探索创新管理模式,旨在通过信息技术、智慧化及移动管理工具集成,优化资源配置与提升管理效率。提出的策略旨在最大化实验室资源效用,加速智慧农业教育与研究进程,推动该领域的持续创新与进步。

“多元基础、分路径培养”的物流大数据应用型人才培养创新与实践

该文从人才培养模式创新、产教融合提升人才培养质量视角,对大数据本科专业应用型人才培养的多元学科专业基础和培养路径做出分析,进而以物流大数据专业群应用型人才培养为例,通过实施文理文工融合改革思路构建物流大数据复合知识体系,建设“多专业+多课程+多层次+多要求”的大数据实践实训平台、多学科专业融合互促的泛在化教学体系和深化产教研融合,形成多元基础分路径培养的人才培养思路并应用实践。通过物流大数据人才培养改革创新与实践,2021—2023年文理文工融合人才培养模式获得认可,教学成果突出,促进学科专业资源整合,形成“资源-名师-成果”互促上升的发展路径,人才培养质量显著提升,社会认可度提高。

科技金融政策、业绩预期差距与企业大数据应用——基于不同期望参照水平的检验

在新一代信息技术和各产业不断融合发展的背景下,如何促进大数据应用成为企业战略决策研究的关键环节.基于企业行为理论和业绩反馈理论,将科技金融试点政策纳入企业探索式创新的前因要素模型,并深入探讨业绩预期差距的调节作用.利用2007—2020年中国A股上市公司数据,基于2011年和2016年多批次科技金融试点政策的自然实验采用倍差法分析发现:科技金融政策具有创新效应,显著提高了试点区域内企业的大数据应用水平;行业业绩期望落差扩大时,企业通过战略变革恢复市场支配力的动机更为强烈,能够正向调节科技金融政策与企业大数据应用之间的关系;历史业绩期望落差扩大时,组织处于不明显的“损失”状态,内部的战略调整动机相对不足.因此,应继续深化改革,推动科技金融政策不断延伸和拓展.同时,在政策推行过程中,企业应进一步完善公司治理结构,充分发挥针对业绩期望落差的内部响应机制.

基于大数据技术的高校学生教育管理平台建设研究

大数据时代的来临为高校教育管理工作创新发展奠定了坚实的技术基础,大数据分析技术的广泛应用为学生管理工作开启了全新的视角。基于对大数据技术赋能高校教育管理工作的价值分析,探寻大数据分析技术在学生管理工作中的具体应用策略,并从技术层面深入探寻基于大数据技术的学生管理平台架构设计,对学生管理平台架构的相关技术和算法进行阐述,旨在为大数据时代背景下,高校学生管理工作应用大数据分析技术提供参考性建议。

大数据管理与应用本科专业学位教育发展状况调查报告(2023)

[目的/意义]开展全国大数据管理与应用专业本科教育的发展状况调查研究,以期反映其发展趋势并提出相应的建议。[研究设计/方法]以开设院校、师资、招生、就业、课程体系和培养目标为六大维度,系统地剖析了我国大数据管理与应用本科教育的现状,并通过与往年数据的比较反映该专业的发展态势。[结论/发现]截至2022年12月,该专业的培养单位数量达到183所。大多数培养单位针对社会需求和自身定位调整其教学,在注重专业实践性的同时,逐步形成自身特色。大多数培养单位的课程体系和培养目标不完全匹配,需要增加对大数据管理和大数据应用方面的课程。[创新/价值]通过全国范围内大数据管理与应用本科专业全面调查和深入分析,反映该专业当前发展现状和存在问题,为此类专业持续发展提供有价值的参考。