Data Warehouse ETL Testing & Data Quality Management A-Z | It Certification Online Course by Udemy

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ETL Testing and Data Quality Management for beginners with practical exercises and certificate of completion.

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Data Warehouse ETL Testing & Data Quality Management A-Z

Learn the essentials of ETL Data Warehouse Testing and Data Quality Managementthrough thisstep-by-step tutorial. This course takes you through the basics of ETL testing, frequently used Data Quality queries, reporting and monitoring. In this tutorial we will learn how to build database views for Data Quality monitoring and build Data Quality visualizations and reports. Learn to build data quality dashboards from scratch. Learn some of the most common mistakes made when performing ETL/ELT tests. Forget about manual ad-hoc ETL testing, learn more about automated ETL and data quality reportsThe course containstraining materials, where you can practice, apply your knowledge and build an appfrom scratch. The training materialsare provided in an Excel file that you can download to your computer. Each module also ends with a short quiz and there is a final quiz at the end of the course. After completion of this course, you will receive acertificateof completion. Good luck and hope you enjoy the course. Pre-requisites: Basic knowledge of SQL Some experience with Visualization tools would be helpful, but not required Basic setup of database (PostgreSQL, Oracle) and visualization tool (Qliksense) is recommendedCourse content: The course consists of the following modules: IntroductionWhat is ETL/ELT Testing and Data Quality Management?Build database views for Data Quality MonitoringBuild dashboards for ReportingExercisesFinal QuizWho should follow this course?Students that want to learn the basics of ETL/ELT testing and Data Quality ManagementBusiness Analysts and Data Analysts that would like to learn more about ETL/ELT testing, frequently used queries and practical examplesSoftware Engineers that would like to build an automated solution for ETL/ELT testing using database views/dashboardsData Stewards and Managers considering to apply data quality standards within their organization

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