Course Code: MAV555
Synopsis
In MAV555 Data Integration for Enterprise Automation, students will learn how to use data integration and workflow automation techniques to drive enterprise transformation and achieve business results. The course begins by giving students an understanding of the roles that integration and automation play in digital transformation, as well as the various integration and automation platforms that have emerged in both Business and Technology environments. Students will learn how to evaluate and select suitable platforms based on business and technical requirements. Following which, students will learn essential concepts, skills and techniques in two common enterprise integration and automation pathways: User Interface-based (UI-based) Automation, like Robotic Process Automation (RPA), and Application Programming Interface-based (API-based) Automation, like Integration Platform-as-a-Service (iPaaS). Students will be guided and equipped with the skills to build their own API-based integration and automation workflows to solve real-life industry problems, and use Artificial Intelligence (AI) and Machine Learning (ML) to enhance their data integration and automation techniques. By the end of this course, students will be competent and proficient in using data integration and automation techniques to build a scalable enterprise integration and automation framework for their organisations. 在MAV555企业自动化数据集成课程中,学生将学习如何利用数据集成和工作流程自动化技术来推动企业转型,实现业务成果。课程开始时,学生将了解集成和自动化在数字化转型中的作用,以及在商业和技术环境中出现的各种集成和自动化平台。学生将学习如何根据业务和技术需求评估和选择合适的平台。接下来,学生将学习两种常见的企业集成和自动化路径中的基本概念、技能和技术:基于用户界面(UI-based)的自动化,例如机器人流程自动化(RPA),以及基于应用程序接口(API-based)的自动化,例如集成平台即服务(iPaaS)。学生将获得指导并掌握构建自己的基于API的集成和自动化工作流程的技能,以解决实际行业问题,并使用人工智能(AI)和机器学习(ML)来增强他们的数据集成和自动化技术。课程结束时,学生将能够熟练运用数据集成和自动化技术,为其组织构建可扩展的企业集成和自动化框架。
Level: 5
Credit Units: 5
Presentation Pattern: EVERY JAN
Topics
- The role of data integration and workflow automation in enterprise transformation 数据集成和工作流程自动化在企业转型中的作用
- Megatrends in data integration and automation 数据集成和自动化的宏观趋势
- Emergence of data integration and automation platforms (messaging, data integration, application integration, process automation, API management) 数据集成和自动化平台的出现(消息传递、数据集成、应用集成、流程自动化、API管理)
- Introduction to User Interface-based (UI-based) Automation 基于用户界面(UI-based)自动化简介
- Introduction to Application Programming Interface-based (API-based) Automation 基于应用程序接口(API-based)自动化简介
- Use of UI-based Automation and API-based Automation in enterprises 企业中UI-based自动化和API-based自动化的应用
- Essentials and best practices of API-based Automation 基于API的自动化的基本要素和最佳实践
- Building API-based integration and automation workflows to solve industry challenges 构建基于API的集成和自动化工作流程以解决行业挑战
- Leveraging Artificial Intelligence (AI) and Machine Learning (ML) to enhance API-based integration and automation workflows 利用人工智能(AI)和机器学习(ML)增强API-based集成和自动化工作流程
- Operating models for data integration and automation in enterprises 企业数据集成和自动化的运营模型
- Designing a scalable enterprise integration and automation framework for organisations 为组织设计一个可扩展的企业集成和自动化框架
- Communicating data integration and automation initiatives to key stakeholders 向关键利益相关者传达数据集成和自动化举措
Learning Outcome
- Assess and select data integration and workflow automation approaches, based on business and technology requirements根据业务和技术需求评估并选择数据集成和工作流程自动化的方法
- Design UI-based Automation and API-based Automation solutions for enterprise environments为企业环境设计基于用户界面和基于应用程序接口的自动化解决方案
- Construct API-based Automation workflows to solve business problems in enterprises, and enhance these workflows with Artificial Intelligence and Machine Learning构建基于API的自动化工作流程以解决企业中的业务问题,并使用人工智能和机器学习增强这些工作流程
- Create a scalable enterprise automation framework to achieve digital transformation in enterprises, and evaluate its success 创建一个可扩展的企业自动化框架以实现数字化转型,并评估其成功性
- Formulate data integration and automation workflows to drive digital transformation, with Application Programming Interface (API), Robotic Process Automation (RPA), Artificial Intelligence (AI) and Machine Learning (ML) 利用应用程序接口(API)、机器人流程自动化(RPA)、人工智能(AI)和机器学习(ML)制定数据集成和自动化工作流程,推动数字化转型
- Construct a scalable enterprise integration and automation practice to solve real-life business problems 构建一个可扩展的企业集成和自动化实践,以解决实际业务问题
- Evaluate the success and outcomes of enterprise integration and automation initiatives in enterprises评估企业集成和自动化举措在企业中的成功和成果