2023 Databricks ETL Automation Testing Complete Guide

所在平台: Udemy

课程主页: https://www.udemy.com/course/2023-databricks-etl-automation-testing-complete-guide/

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课程名称:2023 Databricks ETL 自动化测试完整指南 课程概述:您是否希望通过短时间的培训获得持续的高收入?如果是的话,这个课程将是您的理想选择。随着人工智能和大数据成为工业4.0的驱动力,数据工程师的需求急剧上升,收入也随之增加。转型为数据测试工程师是提高职业收入、享受长期合同和减轻压力的最佳选择之一。 本课程将教您如何从头开始执行实际开放银行项目中的ETL测试,并为您提供可直接使用的强大ETL测试框架和ISTQB测试策略。完成本课程后,您将具备与年薪超过200,000美元的数据测试工程师相似的能力,能够独立解决复杂的ETL测试问题。如果您已经是一名数据测试工程师,本课程将进一步提升您的ETL技巧,节省您在ETL测试过程中的时间和成本,让您获得更多的自由时间。 课程内容包括41节课,大约6.5小时的高质量内容,详细学习以下主题: 第一部分:我们能为您带来的价值 了解完成本课程后您可以掌握的有价值技能,以及额外的免费直播资源以持续学习。 第二部分:Azure Databricks 和 Cosmos DB 设置 能够独立设置Azure Databricks和Cosmos DB并进行连接。 第三部分:ETL项目初始化 从零开始获取真实商业开放银行项目经验,包括抓取业务需求、将其转化为技术需求、设计解决方案和实施。 第四部分:ETL与测试商业目标和测试策略 识别我们要实现的商业目标,并采用正确的测试策略,规划静态测试和左移测试方法。 第五部分:自动化测试框架和解决方案 创建自动化测试框架及其定制测试解决方案,支持多个层次,包括业务逻辑层、数据质量检查层、展示层和数据访问层等。 第六部分:自动化测试解决方案实践 使用定制的测试框架自动化开放银行项目,并作为专家解决复杂的ETL测试问题,如性能、稳定性和可靠性等。 第七部分:测试总结报告的增强和管理 改进和定制测试总结报告,妥善组织测试用例,方便维护和需求可追溯性。 第八部分:数据质量检查和代码重构 为各种数据类型(如日期时间、枚举、正则表达式等)添加数据质量检查功能,进行代码重构,使代码简洁整齐。 通过本课程的学习,您将在数据测试领域提升自己的技能,轻松应对复杂问题,并享受更高的职业回报。

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课程详情

Are you thinking of getting higher income for a long time with a short training period? Then, you come to the right place. As you know AI and big data are the driving forces behind Industry 4.0. Data engineer is high-paid role. As the shortage of data engineers continues and the demand for skilled data engineer is soaring. Switching to data testing engineer is one of the best options for your career, which can get higher pay, long-term contracts and less pressure. By joining this course, you will know how the front-line data engineers execute ETL testing with real open banking project from the scratch, get the ready-to-use, practical and powerful ETL testing framework and the ISTQB testing strategy. So, it will be highly possible to pass your job interview because you really have the similar capabilities with data testing engineers who earn $200, 000+ yearly and be able to resolve complex ETL testing issues on your own after this course.If you are already a data testing engineer, this course will sharpen your ETL skills. This course can free yourself via saving huge amount of computing time and cost during ETL testing process. More importantly, you will get the capabilities of resolving complex issues in terms of performance, stability and reliability. You will enjoy more free time and leave the hard work to the ETL testing framework and scripts.With 41 lectures and about 6.5 hours of high-quality content, you will learn the following topics in depth:Section #1: Values We Can Bring to YouYou will understand what valuable capabilities you can take away after this course and extra free live resources you can keep learning.Section #2: Azure Databricks and Cosmos DB SetupYou are able to set up Azure Databricks, Cosmos DB and connect them on your own. Section #3: ETL Project InitializationGet real commercial open banking project experience from scratch including grabbing business requirement, Coverting it to technical requirement, designing the solution and implementing it.Section #4: ETL and Testing Business Goal and Test StrategyIdentify business goals we are going to achieve and adopt right test strategies and plan static testing and shift-left testing approach.Section #5: Automaton Test Framework and SolutionCreate the automation test framework and implement it with customized test solution. The whole solution will be supported by multiple layers: business logic layer, data quality checking layer, presentation layer, data access layer, etc. Customized, dedicated and ready-to-use functionality has been provided for each layer. They can be reused by you directly or called by third party program. It supports DevOps as well.Section #6: Automation Test Solution PracticeAutomate the open banking project with the customized test framework and resolve complex ETL testing issues in terms of performance, stability and reliability, etc. as an expert.Section #7: Test Summary Report Enhancement and Test ManagementImprove and customize the test summary report and organize test cases properly and make them be easy for maintenance and requirement traceability.Section #8: Data Quality Checking and Code RefractoryAdd the functionality to check data quality for various data types like dateTime, enumeration, regex, etc. Do code refractory to make our code neat and tidy.

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