Data Analytics for Decision Makers 决策数据分析 (MBA519)

MBA519 Data Analytics for Decision Makers presents data analytics as a key modern approach for decision making in business organisations. It examines the key aspects of business analytics based on Cross-Industry Process for Data Mining (CRISP-DM) framework. Students will learn to apply CRISP-DM by going through a series of projects involving data visualisation, association rule mining, clustering, predictive modelling and response modelling. By walking students through such projects, they will gain experience in turning data into important insights that may improve organisational performance. MBA519决策数据分析课程将数据分析视为现代企业决策的重要方法，重点介绍基于跨行业数据挖掘流程（CRISP-DM）框架的商业分析的关键环节。学生将在一系列项目中学习如何应用CRISP-DM方法，包括数据可视化、关联规则挖掘、聚类分析、预测建模及响应建模等内容。通过实践操作，学生将学会把数据转化为有价值的洞见，提升组织绩效。

• Introduction to Business Analytics 商业分析导论
• Overview of CRISP-DM CRISP-DM方法概览
• Introduction to Data Visualisation 数据可视化入门
• Process and Challenges in a Data Visualisation Project 数据可视化项目的流程与挑战
• Association Rule Mining 关联规则挖掘
• Process and Challenges in an Association Rule Mining Project 关联规则挖掘项目的流程与挑战
• Data Clustering 数据聚类分析
• Process and Challenges in a Data Clustering Project 聚类项目的流程与挑战
• Predictive Modelling 预测建模
• Process and Challenges in a Predictive Modelling Project 预测建模项目的流程与挑战
• Response Modelling 响应建模
• Process and Challenges in a Response Modelling Project 响应建模项目的流程与挑战

• Design analytics solutions using the CRISP-DM framework. 运用CRISP-DM框架设计数据分析方案。
• Appraise the suitability of analytics techniques in different contexts. 评估不同情境下分析技术的适用性。
• Evaluate the performance of analytics models. 评估分析模型的效果
• Assess the quality of data for analytics. 评估用于分析的数据质量。
• Prepare data for mining and analysis. 准备数据以进行挖掘与分析。
• Construct an analytics solution using application software. 利用应用软件构建分析解决方案。