Deloitte
6 位校友岗位:Graduate Program · Graduate Consulting · Platform Engineer · Web developer · Platform engineer
BSAN7206
课程定位 BSAN7206(Business Data Management)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 : Relational Data Modelling and SQL - Course overview This topic first introduces relational databases and database management systems. It then introduces conceptual modelling using ER diagram Live session: This session will focus on staff and student introductions, outlining course objectives, reviewing assessments, and discussing conceptual modelling. Self-Directed Learning: Students need to complete this 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 : Relational Data Modelling and SQL - Course overview This topic first introduces relational databases and database management systems. It then introduces conceptual modelling using ER diagram Live session: This session will focus on staff and student introductions, outlining course objectives, reviewing assessments, and discussing conceptual modelling. Self-Directed Learning: Students need to complete this”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 BSAN7206 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 1 : Relational Data Modelling and SQL - Relational Databases and Normalisation This topic introduces the relational model including its main concept and components, integrity constraints, and how ER diagrams can be mapped into relational models. Live Session: Entity Relational Diagrams (ERD), Normalisation, and Structured Query Language (SQL) will be introduced. Self-Directed Learning: Students need to complet 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 : Relational Data Modelling and SQL - Relational Databases and Normalisation This topic introduces the relational model including its main concept and components, integrity constraints, and how ER diagrams can be mapped into relational models. Live Session: Entity Relational Diagrams (ERD), Normalisation, and Structured Query Language (SQL) will be introduced. Self-Directed Learning: Students need to complet”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 BSAN7206 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 1 : Relational Data Modelling and SQL - Introduction to SQL (1) Structured Query Language (SQL) will be presented in more depth. Different types of data retrieval and manipulation will be explored. Live Session: This overview of relational database management systems focuses on their core components and functionalities. It then examines conceptual modeling, introducing the widely used Entity-Relationship (ER) 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 : Relational Data Modelling and SQL - Introduction to SQL (1) Structured Query Language (SQL) will be presented in more depth. Different types of data retrieval and manipulation will be explored. Live Session: This overview of relational database management systems focuses on their core components and functionalities. It then examines conceptual modeling, introducing the widely used Entity-Relationship (ER)”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 BSAN7206 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 2 : Data Warehouse and Dimension Modelling - Introduction to SQL (2) Structured Query Language (SQL) will be presented in more depth. This topic focuses on advanced SQL queries based on subqueries, division and views. Live Session: This session introduces the relational data model and its key concepts in database systems. It then examines integrity constraints that ensure data consistency, and concludes with t 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 : Data Warehouse and Dimension Modelling - Introduction to SQL (2) Structured Query Language (SQL) will be presented in more depth. This topic focuses on advanced SQL queries based on subqueries, division and views. Live Session: This session introduces the relational data model and its key concepts in database systems. It then examines integrity constraints that ensure data consistency, and concludes with t”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 BSAN7206 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 2 : Data Warehouse and Dimension Modelling - Dimension Modelling This topic focuses on concepts related to data redundancies, data anomalies, data normalization, need for data denormalization, introduction to Data Warehouse, Star Schema, and creation of dimension models. Live Session: This section introduces the dimensional model, a core design approach in analytical systems and data warehouses. It organises d 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 : Data Warehouse and Dimension Modelling - Dimension Modelling This topic focuses on concepts related to data redundancies, data anomalies, data normalization, need for data denormalization, introduction to Data Warehouse, Star Schema, and creation of dimension models. Live Session: This section introduces the dimensional model, a core design approach in analytical systems and data warehouses. It organises d”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 BSAN7206 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 2 : Data Warehouse and Dimension Modelling - Advanced Dimension Modelling This topics focus on various techniques for creating facts and dimension tables data warehouse architecture, Extract transformation load (ETL), and Microsoft SQL Server integration services (SSIS) tutorial. denormalization, introduction to Data Warehouse, Star Schema, and creation of dimension models. Live Session: This session explores 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 : Data Warehouse and Dimension Modelling - Advanced Dimension Modelling This topics focus on various techniques for creating facts and dimension tables data warehouse architecture, Extract transformation load (ETL), and Microsoft SQL Server integration services (SSIS) tutorial. denormalization, introduction to Data Warehouse, Star Schema, and creation of dimension models. Live Session: This session explores”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 BSAN7206 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 2 : Data Warehouse and Dimension Modelling - ETL and Metadata This topics focus on various techniques for creating facts and dimension tables data warehouse architecture, Extract transformation load (ETL), and Microsoft SQL Server integration services (SSIS) tutorial. denormalization, introduction to Data Warehouse, Star Schema, and creation of dimension models. Live Session: This session provides a high-level 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 : Data Warehouse and Dimension Modelling - ETL and Metadata This topics focus on various techniques for creating facts and dimension tables data warehouse architecture, Extract transformation load (ETL), and Microsoft SQL Server integration services (SSIS) tutorial. denormalization, introduction to Data Warehouse, Star Schema, and creation of dimension models. Live Session: This session provides a high-level”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 BSAN7206 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 2 : Data Warehouse and Dimension Modelling - ETL and Metadata This topics focus on various techniques for creating facts and dimension tables data warehouse architecture, Extract transformation load (ETL), and Microsoft SQL Server integration services (SSIS) tutorial. denormalization, introduction to Data Warehouse, Star Schema, and creation of dimension models. Live Session: This session presents a deeper vie 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 : Data Warehouse and Dimension Modelling - ETL and Metadata This topics focus on various techniques for creating facts and dimension tables data warehouse architecture, Extract transformation load (ETL), and Microsoft SQL Server integration services (SSIS) tutorial. denormalization, introduction to Data Warehouse, Star Schema, and creation of dimension models. Live Session: This session presents a deeper vie”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 BSAN7206 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:Module 2 : Data Warehouse and Dimension Modelling - Data Warehouse Architecture and ETL This topic focuses on concepts related to data redundancies, data anomalies, data normalization, need for data denormalization, introduction to Data Warehouse, Star Schema, and creation of dimension models. Live Session: This session provides a deeper exploration of data warehouse architecture, focusing on design strategies and th 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 : Data Warehouse and Dimension Modelling - Data Warehouse Architecture and ETL This topic focuses on concepts related to data redundancies, data anomalies, data normalization, need for data denormalization, introduction to Data Warehouse, Star Schema, and creation of dimension models. Live Session: This session provides a deeper exploration of data warehouse architecture, focusing on design strategies and th”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 BSAN7206 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 3 : Data@Scale - NoSQL in Document-Oriented Databases and MongoDB Data Model Design and Implementation This topic introduces NoSQL as a solution to the challenges of Big Data, focusing on document-oriented databases. It examines when and why NoSQL is preferred over traditional relational databases, and explores MongoDB as a practical example for handling flexible, scalable data models. Live Session : NoSQL dat 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 : Data@Scale - NoSQL in Document-Oriented Databases and MongoDB Data Model Design and Implementation This topic introduces NoSQL as a solution to the challenges of Big Data, focusing on document-oriented databases. It examines when and why NoSQL is preferred over traditional relational databases, and explores MongoDB as a practical example for handling flexible, scalable data models. Live Session : NoSQL dat”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 BSAN7206 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 3 : Data@Scale - Big Data This topic presents an introduction to Big Data including scenarios and discusses the CAP (consistency, availability, and partition) theorem and its implications on the capabilities and limitations of big data systems. Live Session : Data at Scale, Data Centres, Big Data Applications, Case Study, Real-time Analytics, Distributed Systems,CAP Theorem Self-Directed Learning: Students nee 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 : Data@Scale - Big Data This topic presents an introduction to Big Data including scenarios and discusses the CAP (consistency, availability, and partition) theorem and its implications on the capabilities and limitations of big data systems. Live Session : Data at Scale, Data Centres, Big Data Applications, Case Study, Real-time Analytics, Distributed Systems,CAP Theorem Self-Directed Learning: Students nee”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 BSAN7206 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 3 : Data@Scale - Data Volume, Streams and Graphs This topic presents system architectures to process big data including, for example, Map/Reduce and Apache Spark. Live Session: MapReduce Evolution, Apache Spark, Languages/Interfaces, RDD (Resilient Distributed Dataset), Spark Streaming, DStreams, Window Operations, Spark GraphX Self-Directed Learning: Students need to complete this weeks self-directed material 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 : Data@Scale - Data Volume, Streams and Graphs This topic presents system architectures to process big data including, for example, Map/Reduce and Apache Spark. Live Session: MapReduce Evolution, Apache Spark, Languages/Interfaces, RDD (Resilient Distributed Dataset), Spark Streaming, DStreams, Window Operations, Spark GraphX Self-Directed Learning: Students need to complete this weeks self-directed material”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 BSAN7206 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 3 : Data@Scale - Revision This course has covered key concepts in relational databases, data warehousing, and big data technologies. It introduces the relational data model, dimensional modeling, and data warehouse design, including ETL processes and metadata management. Students explore practical tools like Microsoft SSIS and learn about NoSQL databases, focusing on MongoDB. The course also addresses big data 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 : Data@Scale - Revision This course has covered key concepts in relational databases, data warehousing, and big data technologies. It introduces the relational data model, dimensional modeling, and data warehouse design, including ETL processes and metadata management. Students explore practical tools like Microsoft SSIS and learn about NoSQL databases, focusing on MongoDB. The course also addresses big data”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 BSAN7206 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 BSAN7206 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 BSAN7206 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。