数据工程全栈班15期 Final Demo | Team ACE 项目展示 | 澳洲 IT

The business goal of this project is to build an intelligent recommendation system to improve the market sales efficiency of products by analyzing and processing more than three million orders and sales data of online retailers. This project comprehensively covers the core processes of business data analysis - starting from demand analysis, gradually deepening data processing, data architecture design, machine learning modeling and visual analysis. In this project, students will learn how to build databases and data streams on the AWS cloud, use big data tools for data conversion and processing, conduct in-depth data analysis and train models, and finally productize the project and create business value. You will master how to use S3 on AWS to build a data lake, use AWS Athena and Lambda Function to process data, and build a complete data process through Step Functions and Spark, and finally use SageMaker and API Gateway to develop data product applications. This project involves multiple data files and combines multiple cloud solutions to provide practical experience with both breadth and depth in data processing and modeling, simulating data challenges in real business environments. The experience accumulated by students through this project can be directly applied to actual work and improve their competitiveness in data analysis and cloud computing. 该项目的商业目标是通过分析和处理网络零售商超过三百万条订单和销售数据，构建一个智能推荐系统，以提升产品的市场销售效率。该项目全面涵盖了商业数据分析的核心流程——从需求分析入手，逐步深入数据处理、数据架构设计、机器学习建模及可视化分析。 在本项目中，学生将学习如何在AWS云端构建数据库和数据流，利用大数据工具进行数据转换与处理，进行深度数据分析并训练模型，最终将项目产品化并创造商业价值。你将掌握如何在AWS上使用S3构建数据湖，利用AWS Athena和Lambda Function处理数据，并通过Step Functions和Spark搭建完整的数据流程，最终使用SageMaker和API Gateway开发数据产品应用。 本项目涉及多个数据文件，并结合多种云端解决方案，在数据处理和建模过程中提供广度与深度兼备的实战经验，模拟真实商业环境中的数据挑战。学生通过该项目积累的经验，可直接应用于实际工作，提升在数据分析与云计算领域的竞争力。