1
课程详述
COURSE SPECIFICATION
以下课程信息可能根据实际授课需要或在课程检讨之后产生变动。如对课程有任何疑问，请联
系授课教师。
The course information as follows may be subject to change, either during the session because of unforeseen
circumstances, or following review of the course at the end of the session. Queries about the course should be
directed to the course instructor.
1.
课程名称 Course Title
大数据管理与应用前沿讲堂 Lectures on the Frontiers of Big Data Management and
Applications
2.
授课院系
Originating Department
商学院 School of Business
3.
课程编号
Course Code
EBA103
4.
课程学分 Credit Value
2
5.
课程类别
Course Type
专业选修课 Professional Elective Courses
6.
授课学期
Semester
春季 Spring
7.
授课语言
Teaching Language
中英双语 English & Chinese
8.
授课教师、所属学系、联系方
式（如属团队授课，请列明其
他授课教师）
Instructor(s), Affiliation&
Contact
（For team teaching, please list
all instructors）
黄伟，商学院，hw-feba@sustech.edu.cn
江俊毅，商学院，jiangjy@sustech.edu.cn
何翘楚，商学院，heqc@sustech.edu.cn
李少波，商学院，lisb3@sustech.edu.cn
郭悦，商学院，guoy@sustech.edu.cn
雷洋，商学院，leiy@sustech.edu.cn
李媛媛，商学院，liyy3@sustech.edu.cn
顾里一，商学院，guly@sustech.edu.cn
Moris Strub，商学院，strub@sustech.edu.cn
叶茂亮，商学院，maoliang.ye@xmu.edu.cn
9.
实验员/助教、所属学系、联系
方式
Tutor/TA(s), Contact
无 NA
10.
选课人数限额(可不填)
Maximum Enrolment
（Optional）
2
授课方式
Delivery Method
讲授
Lectures
习题/辅导/讨论
Tutorials
实验/实习
Lab/Practical
其它(请具体注明)
Other（Please specify）
总学时
Total
11.
学时数
Credit Hours
32
32
12.
先修课程、其它学习要求
Pre-requisites or Other
Academic Requirements
无 None
13.
后续课程、其它学习规划
Courses for which this course
is a pre-requisite
无 None
14.
其它要求修读本课程的学系
Cross-listing Dept.
无 None
教学大纲及教学日历 SYLLABUS
15.
教学目标 Course Objectives
本课程旨在向对大数据管理与应用专业感兴趣的学生介绍大数据管理最前沿的研究，分享业界最新的应用；培养数据管理
和商务分析人才。通过本课程，有助于学生了解大数据行业和研究的趋势，对自身未来的学科发展进行初步规划。
This course aims to introduce the cutting-edge research of big data management and share the latest applications of the
industry to students who are interested in big data technology and management. With the help of this course, our final
gaol is to cultivate data management and business analysis talents. Through this course, students can understand
industry and research trends and make preliminary plans for future development.
16.
预达学习成果 Learning Outcomes
通过对本课程的学习，学生将对大数据管理与应用相关前沿研究产生一个整体认知，对于行业内著名企业在大数据上的应
用有一定了解，启发学生对未来发展进行规划。
Through the study of this course, students will have an overall understanding of the cutting-edge research
related to big data, have a brief understanding of the applications of big data by famous enterprises in
the industry. And this course will inspire students to plan their future development.
17.
课程内容及教学日历 （如授课语言以英文为主，则课程内容介绍可以用英文；如团队教学或模块教学，教学日历须注明
主讲人）
Course Contents (in Parts/Chapters/Sections/Weeks. Please notify name of instructor for course section(s), if
this is a team teaching or module course.)
3
星期
Week
主题
Topic
主讲人
Speaker
简介
Brief Introduction
1
“顶天立地“——大数据研究方向
的确定（The Determination of the
Research Direction of Big Data）
黄伟
大数据是交叉学科研究领域（跨管理科学和工商管
理等学科），涉及的研究问题和方向多且广，不易
确定具体的研究方向。本课程讲介绍 “顶天立地”
的研究方向如何确定。“顶天”的大数据研究即探
讨新涌现的首席数据执行官（CDO）如何将组织中
高层决策从经验导向型改变为数据导向型，从而使
组织高管能在大数据时代带领组织更上一层楼。
“立地”的大数据研究即数据质量的研究，这也是
大数据研究的基石。
Big data is an interdisciplinary research field
(spanning management science, business
administration and other disciplines), involving a
wide range of research issues and directions, and it
is difficult to determine the specific research
direction. This course introduces how to determine
the research direction of "Dingtian Lidi". "Dingtian"
means that the big data research explores how the
newly emerged chief data executive (CDO)
changes the decision-making of middle and senior
level of the organization from experience-oriented
to data-oriented, so that the senior management of
the organization can lead the organization to a
higher level in the era of big data. "Lidi" means that
the research of data quality is the cornerstone of
big data research.
2
项目管理视角下的组织战略变革
（Organizational Strategical
Change from the Perspective of
Project Management）
江俊毅
基于系统性观点实现组织战略目标，关注战略变革
与整合、不确定性与模糊性中潜在收益、机会最大
化，提供结构化项目管理方法。
Achieve the organization's strategic goals based on
a systematic perspective, focus on strategic
change and integration, maximize potential benefits
and opportunities in uncertainty and ambiguity, and
provide structured project management methods.
3
数据驱动的物流科技与服务运营管
理（Data-driven Logistics
Technology and Service Operation
Management）
何翘楚
运筹学和运营管理方法在主要的物流科技公司（阿
里，京东，顺丰等）和平台经济公司（滴滴出行
等）有广泛的应用。这节课将系统介绍数据科学在
这类应用中的角色：如何将运筹优化算法，统计机
器学习和经济管理分析方法整合起来提高企业运营
效率。
Operations research and operation management
methods are widely used in logistics technology
companies (Ali, JD, SF express, etc.) and platform
economy companies (Didi Chuxing, etc.). This
speech will systematically introduce the role of data
science in such applications as how to integrate
operational optimization algorithms, statistical
machine learning, and economic management
analysis methods to improve the operational
efficiency of enterprises.
4
大数据背景下的行为科学
（Behavioral science in the context
of big data）
李少波
这一话题将从最近几年的诺贝尔经济学奖得主的研
究切入，探讨大数据背景下行为科学的发展趋势和
未来走向。
Starting from the research of Nobel Prize winners