|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/automation-in-etl-data-testing/
课程评论：没有评论
**课程名称：** ETL/数据测试自动化 **课程概述：** 本课程旨在介绍ETL测试或数据测试自动化的基本概念。在项目或发布过程中，我们常常需要执行重测和（非）回归测试，即重复执行相同的验证步骤，以确保近期变更不会引入回归问题。掌握自动化这些重复性任务的思路，将极大地节省人力和时间。 课程以一个简单的ETL项目为例，演示自动化测试的步骤。具体实现上，课程使用Python和Pytest来组织测试用例。该示例项目旨在帮助您理解在实际工作中如何将自动化测试与实际需求相结合。请注意，这只是一个示例项目，实际的ETL项目可能与之有很大差异。 为了验证业务规则，课程中使用了SQL查询。课程也创建了一些框架，可用于后续的测试用例编写和执行。课程中的大多数测试用例并非详尽无遗，仅用于理解目的，不应作为ETL测试的唯一参考。本课程的主要收获是如何实现相同验证步骤的自动化。 **推荐学习基础：** * ETL测试经验 * SQL基础知识 * Python基础知识 * Pytest基础知识 即使您对上述内容没有太多经验，也能够相对轻松地理解本课程，因为课程内容力求简洁易懂。
The course is on a basic idea of automation in ETL Testing or Data Testing. We perform Retesting and (Non) Regression tests during a project or release. We perform same set of validation steps to ensure there are no regression introduced due to recent changes. If one has the idea on automating those repetitive task, it helps a lot to save our efforts and time.I have used a simple ETL project to understand the automation steps. In this course, I have used Python and Pytest to organize the test cases. The project used is just to give an idea how can we connect to actual requirement when we perform actual testing during our professional work. The project is not ideal and actual ETL project can vary to a greater extent.To validate the business rules, I have used SQL queries in the course. Few frameworks are created to use it for further test cases and execution. Most of the test cases include here are not exhaustive and are just for understanding purpose. Please do not take it as a reference for ETL Testing. Only take away from this course is how to automate your same set of validation steps.It is recommended to have experience on ETL Testing and basic knowledge of SQL, Python and Pytest. However, if you don't have much experience on these, it won't be very difficult to understand it. I have tried to make the course as simple as possible.
