商业分析课程

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。