Deloitte
6 位校友岗位:Graduate Program · Graduate Consulting · Platform Engineer · Web developer · Platform engineer
BSAN7205
课程定位 BSAN7205(Business Analytics Foundations)是 UQ 商业分析方向的重要课程,核心目标是把课堂框架转化为真实场景中的判断与交付能力。课程通常连接基础方法与高阶专题,既服务后续课程学习,也直接对应实习与职场中的分析、沟通和协作任务。 技术栈与学习内容 课程内容通常覆盖数据解读、业务分析、研究方法、案例推理与商业表达,并结合 Excel/统计工具、报告写作和展示训练。你需要掌握的不只是知识点本身,还包括问题拆解、证据组织、结论表达和风险说明。 课程结构 课程一般按 13 周推进,前段建立框架,中段强化案例与作业,后段综合评估。考核常见组合为 Quiz/Tutorial、作业/报告、展示和期末评估。评分不仅看结果正确性,也看逻辑完整性、表达清晰度和可执行性。 适合人群 适合希望提升分析思维、商业表达和项目协作能力的同学,尤其适合走分析、运营、咨询、管理或研究方向。建议每周投入 8-12 小时,保持“预习-练习-复盘”节奏,持续输出比临时冲刺更稳。
Course decision
先看考核重心、截止节奏和入门要求,再决定这门课是否适合你的学期安排。
考核总权重
100%
4 项考核
最高单项
35%
Case Assignment
期末考试
有
以官方 outline 为准
Hurdle
未列出
当前考核表没有 Hurdle 标记
What you learn
学习成果来自官方 Unit Outline,关键词来自这门课的逐周主题。
Syllabus
默认只展示每周独有的知识重点;节奏、考核、Tutorial 和避坑信息按需展开。
第1周主题:Module 1.1: The Data Race Framework This topic builds on a practical framework called Data Race to explain how businesses can create value from their digital data assets. Live Welcome Session: This session will focus on staff and student introductions, outlining course objectives, reviewing assessments, and discussing the Data Race Framework. Self-directed learning : Students need to complete this week's self-directe 本周先完成 Lecture/Reading 的概念梳理,再用 tutorial 或题目验证理解,重点是把概念转成可解释的步骤。 学习重点:围绕“Module 1.1: The Data Race Framework This topic builds on a practical framework called Data Race to explain how businesses can create value from their digital data assets. Live Welcome Session: This session will focus on staff and student introductions, outlining course objectives, reviewing assessments, and discussing the Data Race Framework. Self-directed learning : Students need to complete this week's self-directe”识别关键术语、方法边界和常见误区,输出一页结构化笔记(定义、方法、例题、易错点)。 实操建议:至少完成 2-3 个与本周主题直接相关的练习,并记录每题的假设与推导过程,避免只记结论。 交付与复盘:对照 BSAN7205 的 assessment 要求检查本周产出,保留可复用模板用于后续周和考前复盘。
第2周主题:Module 2.1: Business Purpose This topic focuses on how companies can formulate analytics business cases, using a user-centric approach. Live Case Analysis Session: This case analysis session focuses on the journey of IDEO, a design thinking firm, and how their approaches can be used to develop user-centric analytics solutions. Preparation : Students need to read and analyse the case study before the live session and 本周先完成 Lecture/Reading 的概念梳理,再用 tutorial 或题目验证理解,重点是把概念转成可解释的步骤。 学习重点:围绕“Module 2.1: Business Purpose This topic focuses on how companies can formulate analytics business cases, using a user-centric approach. Live Case Analysis Session: This case analysis session focuses on the journey of IDEO, a design thinking firm, and how their approaches can be used to develop user-centric analytics solutions. Preparation : Students need to read and analyse the case study before the live session and”识别关键术语、方法边界和常见误区,输出一页结构化笔记(定义、方法、例题、易错点)。 实操建议:至少完成 2-3 个与本周主题直接相关的练习,并记录每题的假设与推导过程,避免只记结论。 交付与复盘:对照 BSAN7205 的 assessment 要求检查本周产出,保留可复用模板用于后续周和考前复盘。
第3周主题:Module 2.1: Business Purpose (continued) The focus on this week is to progress the project work and unpack the business problem. Live Industry Session: The session gives students opportunity to ask assignment-1 data related questions to Aginic employees. Self-Directed Learning: Students need to work on assignment 1 and prepare questions for the industry session. 本周先完成 Lecture/Reading 的概念梳理,再用 tutorial 或题目验证理解,重点是把概念转成可解释的步骤。 学习重点:围绕“Module 2.1: Business Purpose (continued) The focus on this week is to progress the project work and unpack the business problem. Live Industry Session: The session gives students opportunity to ask assignment-1 data related questions to Aginic employees. Self-Directed Learning: Students need to work on assignment 1 and prepare questions for the industry session.”识别关键术语、方法边界和常见误区,输出一页结构化笔记(定义、方法、例题、易错点)。 实操建议:至少完成 2-3 个与本周主题直接相关的练习,并记录每题的假设与推导过程,避免只记结论。 交付与复盘:对照 BSAN7205 的 assessment 要求检查本周产出,保留可复用模板用于后续周和考前复盘。
第4周主题:Module 3.1: Understanding Data This topic takes a deep dive into understanding data, its evolution, data sources and types, data's quality issues and meta data. Live Case Analysis Session: This session provides a discussion on the cases of Netflix and Walmart and how they explore their data assets to generate value for users. Self-Directed Learning: Students need to complete this week's self-directed material before 本周先完成 Lecture/Reading 的概念梳理,再用 tutorial 或题目验证理解,重点是把概念转成可解释的步骤。 学习重点:围绕“Module 3.1: Understanding Data This topic takes a deep dive into understanding data, its evolution, data sources and types, data's quality issues and meta data. Live Case Analysis Session: This session provides a discussion on the cases of Netflix and Walmart and how they explore their data assets to generate value for users. Self-Directed Learning: Students need to complete this week's self-directed material before”识别关键术语、方法边界和常见误区,输出一页结构化笔记(定义、方法、例题、易错点)。 实操建议:至少完成 2-3 个与本周主题直接相关的练习,并记录每题的假设与推导过程,避免只记结论。 交付与复盘:对照 BSAN7205 的 assessment 要求检查本周产出,保留可复用模板用于后续周和考前复盘。
第5周主题:Module 3.1 (Continued): Coding Bootcamp Prep This topic uses a hands-on programming approach to demonstrate how data can be explored and transformed to make it fit for use. Live Coding Bootcamp Session (Prep): This session will introduce you to the Python coding environment in Jupyter Notebook. Self-Directed Material: Students need to complete this week's self-directed material before the live session. | Module 3.1 ( 本周先完成 Lecture/Reading 的概念梳理,再用 tutorial 或题目验证理解,重点是把概念转成可解释的步骤。 学习重点:围绕“Module 3.1 (Continued): Coding Bootcamp Prep This topic uses a hands-on programming approach to demonstrate how data can be explored and transformed to make it fit for use. Live Coding Bootcamp Session (Prep): This session will introduce you to the Python coding environment in Jupyter Notebook. Self-Directed Material: Students need to complete this week's self-directed material before the live session. | Module 3.1 (”识别关键术语、方法边界和常见误区,输出一页结构化笔记(定义、方法、例题、易错点)。 实操建议:至少完成 2-3 个与本周主题直接相关的练习,并记录每题的假设与推导过程,避免只记结论。 交付与复盘:对照 BSAN7205 的 assessment 要求检查本周产出,保留可复用模板用于后续周和考前复盘。
第6周主题:Module 3.2: Exploring Data (Coding Bootcamp 1) This module introduces you to techniques to identify and address data quality issues in your data. Live Coding Bootcamp Session: This session will introduce you to how to explore data using Python. Self-Directed Learning: You will need to work through the self-directed learning material for this module. | Module 3.2 (Continued): Coding Practice 1a This session is to help 本周先完成 Lecture/Reading 的概念梳理,再用 tutorial 或题目验证理解,重点是把概念转成可解释的步骤。 学习重点:围绕“Module 3.2: Exploring Data (Coding Bootcamp 1) This module introduces you to techniques to identify and address data quality issues in your data. Live Coding Bootcamp Session: This session will introduce you to how to explore data using Python. Self-Directed Learning: You will need to work through the self-directed learning material for this module. | Module 3.2 (Continued): Coding Practice 1a This session is to help”识别关键术语、方法边界和常见误区,输出一页结构化笔记(定义、方法、例题、易错点)。 实操建议:至少完成 2-3 个与本周主题直接相关的练习,并记录每题的假设与推导过程,避免只记结论。 交付与复盘:对照 BSAN7205 的 assessment 要求检查本周产出,保留可复用模板用于后续周和考前复盘。
第7周主题:Module 3.3: Transforming Data (Coding Bootcamp 2) Module 3.3 is the final topic for the second step in the Data Race, focusing on Transforming Data. Live Coding Bootcamp Session: This session is a coding bootcamp focusing on using Python for data transformations. Self-Directed Learning: You will need to work through the self-directed learning material for this module. | Module 3.3 (Continued): Coding Practice 2a | Mo 本周先完成 Lecture/Reading 的概念梳理,再用 tutorial 或题目验证理解,重点是把概念转成可解释的步骤。 学习重点:围绕“Module 3.3: Transforming Data (Coding Bootcamp 2) Module 3.3 is the final topic for the second step in the Data Race, focusing on Transforming Data. Live Coding Bootcamp Session: This session is a coding bootcamp focusing on using Python for data transformations. Self-Directed Learning: You will need to work through the self-directed learning material for this module. | Module 3.3 (Continued): Coding Practice 2a | Mo”识别关键术语、方法边界和常见误区,输出一页结构化笔记(定义、方法、例题、易错点)。 实操建议:至少完成 2-3 个与本周主题直接相关的练习,并记录每题的假设与推导过程,避免只记结论。 交付与复盘:对照 BSAN7205 的 assessment 要求检查本周产出,保留可复用模板用于后续周和考前复盘。
第8周主题:Module 4.1: Performance Management (Coding Bootcamp 3) This Module describes how data and analytics can help companies manage their business performance. Live Coding Bootcamp Session: This session is a coding bootcamp focusing on using Python for generate insights from the data. Self-Directed Learning: You will need to work through the self-directed learning material for this module. | Module 4.1 (Continued): Coding 本周先完成 Lecture/Reading 的概念梳理,再用 tutorial 或题目验证理解,重点是把概念转成可解释的步骤。 学习重点:围绕“Module 4.1: Performance Management (Coding Bootcamp 3) This Module describes how data and analytics can help companies manage their business performance. Live Coding Bootcamp Session: This session is a coding bootcamp focusing on using Python for generate insights from the data. Self-Directed Learning: You will need to work through the self-directed learning material for this module. | Module 4.1 (Continued): Coding”识别关键术语、方法边界和常见误区,输出一页结构化笔记(定义、方法、例题、易错点)。 实操建议:至少完成 2-3 个与本周主题直接相关的练习,并记录每题的假设与推导过程,避免只记结论。 交付与复盘:对照 BSAN7205 的 assessment 要求检查本周产出,保留可复用模板用于后续周和考前复盘。
第9周主题:Assessment 2 Q&A Session 1a This session will help you practice your coding skills and prepare for Assignment 2 submission. | Assessment 2 Q&A Session 1b This session will help you practice your coding skills and prepare for Assignment 2 submission. 本周先完成 Lecture/Reading 的概念梳理,再用 tutorial 或题目验证理解,重点是把概念转成可解释的步骤。 学习重点:围绕“Assessment 2 Q&A Session 1a This session will help you practice your coding skills and prepare for Assignment 2 submission. | Assessment 2 Q&A Session 1b This session will help you practice your coding skills and prepare for Assignment 2 submission.”识别关键术语、方法边界和常见误区,输出一页结构化笔记(定义、方法、例题、易错点)。 实操建议:至少完成 2-3 个与本周主题直接相关的练习,并记录每题的假设与推导过程,避免只记结论。 交付与复盘:对照 BSAN7205 的 assessment 要求检查本周产出,保留可复用模板用于后续周和考前复盘。
第10周主题:Module 4.2: Introduction to Machine Learning This topic explains the process of machines learning, together with a number of machine learning algorithms and how they are used in business. | Module 4.2 (Continued): Dashboarding workshop 1a This session provides a hands-on experience to build digital dashboards with a popular tool. Labour Day Public Holiday - Monday 4th May 2026 - Check Blackboard for announcements abo 本周先完成 Lecture/Reading 的概念梳理,再用 tutorial 或题目验证理解,重点是把概念转成可解释的步骤。 学习重点:围绕“Module 4.2: Introduction to Machine Learning This topic explains the process of machines learning, together with a number of machine learning algorithms and how they are used in business. | Module 4.2 (Continued): Dashboarding workshop 1a This session provides a hands-on experience to build digital dashboards with a popular tool. Labour Day Public Holiday - Monday 4th May 2026 - Check Blackboard for announcements abo”识别关键术语、方法边界和常见误区,输出一页结构化笔记(定义、方法、例题、易错点)。 实操建议:至少完成 2-3 个与本周主题直接相关的练习,并记录每题的假设与推导过程,避免只记结论。 交付与复盘:对照 BSAN7205 的 assessment 要求检查本周产出,保留可复用模板用于后续周和考前复盘。
第11周主题:Module 4.3 & 4.4: Visual Storytelling and Data-driven Action This topic shows how analytics professionals can build effective narratives that influence their audience and inspire competitive action or automation of business processes. Live Session: This session will focus on trust in data and how best inspire action based on data-driven insights. Self-Directed Learning: You will need to work through the self-directed 本周先完成 Lecture/Reading 的概念梳理,再用 tutorial 或题目验证理解,重点是把概念转成可解释的步骤。 学习重点:围绕“Module 4.3 & 4.4: Visual Storytelling and Data-driven Action This topic shows how analytics professionals can build effective narratives that influence their audience and inspire competitive action or automation of business processes. Live Session: This session will focus on trust in data and how best inspire action based on data-driven insights. Self-Directed Learning: You will need to work through the self-directed”识别关键术语、方法边界和常见误区,输出一页结构化笔记(定义、方法、例题、易错点)。 实操建议:至少完成 2-3 个与本周主题直接相关的练习,并记录每题的假设与推导过程,避免只记结论。 交付与复盘:对照 BSAN7205 的 assessment 要求检查本周产出,保留可复用模板用于后续周和考前复盘。
第12周主题:Module 5.1: Value This module explains how analytics value can be defined and measured and how its negetive consequences can be avoided. Live session: This session will discuss the Guess case study and how they measured analytics value. It will also involve a discussion of surveillance captalism By Shoshana Zuboff. Self-Directed Learning: You will need to work through the self-directed learning material for this modu 本周先完成 Lecture/Reading 的概念梳理,再用 tutorial 或题目验证理解,重点是把概念转成可解释的步骤。 学习重点:围绕“Module 5.1: Value This module explains how analytics value can be defined and measured and how its negetive consequences can be avoided. Live session: This session will discuss the Guess case study and how they measured analytics value. It will also involve a discussion of surveillance captalism By Shoshana Zuboff. Self-Directed Learning: You will need to work through the self-directed learning material for this modu”识别关键术语、方法边界和常见误区,输出一页结构化笔记(定义、方法、例题、易错点)。 实操建议:至少完成 2-3 个与本周主题直接相关的练习,并记录每题的假设与推导过程,避免只记结论。 交付与复盘:对照 BSAN7205 的 assessment 要求检查本周产出,保留可复用模板用于后续周和考前复盘。
第13周主题:Module 6.1: Becoming Data Savvy This is a revision week and will include Q&A session for Assignment 3. | Module 6.1: Becoming Data Savvy (Continued) This is a revision week and will include Q&A session for Assignment 3. 本周先完成 Lecture/Reading 的概念梳理,再用 tutorial 或题目验证理解,重点是把概念转成可解释的步骤。 学习重点:围绕“Module 6.1: Becoming Data Savvy This is a revision week and will include Q&A session for Assignment 3. | Module 6.1: Becoming Data Savvy (Continued) This is a revision week and will include Q&A session for Assignment 3.”识别关键术语、方法边界和常见误区,输出一页结构化笔记(定义、方法、例题、易错点)。 实操建议:至少完成 2-3 个与本周主题直接相关的练习,并记录每题的假设与推导过程,避免只记结论。 交付与复盘:对照 BSAN7205 的 assessment 要求检查本周产出,保留可复用模板用于后续周和考前复盘。
Assessment
Quiz / Tutorial
检验 BSAN7205 阶段掌握。
Case Assignment
案例分析或报告作业。
Presentation / Project
展示与协作能力评估。
Final Exam / Final Assessment
期末综合评估。
Assignments
完成 BSAN7205 的核心案例分析任务。
重点: 框架应用与证据组织
要求:提交结构化报告
⏱ 预计 12 小时
完成综合问题分析并输出可执行建议。
重点: 结论表达与风险评估
要求:提交报告/展示材料
⏱ 预计 16 小时
From Seniors
基础信息谁都查得到,真正值钱的是过来人的经验。
比你早一年的学长留下的真实经验 —— ChatGPT 给不了。
这门课还没有学长经验,你可以是第一个 —— 注册后在课内分享。
这门课暂无往年考点记录。
下面是匠人学院毕业生整体去过的公司分布(来自脱敏校友证言)。这是全平台的总体去向,不代表选这门课的人一定去这些公司。
统计自 317 份脱敏校友证言
岗位:Graduate Program · Graduate Consulting · Platform Engineer · Web developer · Platform engineer
岗位:Frontend Dev · junior frontend developer · Front-end Developer · Full Stack Developer
岗位:Full-stack Developer · Data Engineer · Consultant
关于这块数据,我们说实话
雇主墙来自脱敏毕业生证言(testimonials)的整体分布,无法关联到具体学员或其所选课程;仅作为毕业生去向的总体社会证明展示。
我们没有"某位学长选了这门课、后来进了哪家公司"这种可查询的个人去向档案 —— 校友证言是脱敏的,无法关联到具体的人或他选过的课。所以这里只给整体分布,不给个人路径,不编。