Building frameworks is now an industry norm and it has become an important skill to know how to visualize, design, plan, and implement data frameworks. The framework that we are going to build together is the Metadata-Driven Ingestion Framework. Metadata-driven frameworks allow a company to develop the system just once and it can be adopted and reused by various business clusters without the need for additional development, thus saving the business time and costs. Think of it as a plug-and-play system.
The first objective of the course is to onboard you onto the Azure Data Factory platform to help you assemble your first Azure Data Factory pipeline. Once you get a good grip on the Azure Data Factory development pattern, then it becomes easier to adopt the same pattern to onboard other sources and data sinks.
Once you are comfortable with building a basic Azure Data Factory pipeline, as a second objective, we then move on to building a fully-fledged and working metadata-driven framework to make the ingestion more dynamic; furthermore, we will build the framework in such a way that you can audit every batch orchestration and individual pipeline runs for business intelligence and operational monitoring.
By the end of this course, you will be able to design, implement, and get production-ready for data ingestion in Azure.
All the resource files are added to the GitHub repository at: https://github.com/PacktPublishing/Azure-Data-Factory-for-Beginners---B…
Learn about Azure Data Factory and Azure Blob Storage
Understand data engineering, data lake, and metadata-driven frameworks concepts
Look at the industry-based example of how to build ingestion frameworks
Learn dynamic Azure Data Factory pipelines and email notifications with logic apps
Study tracking of pipelines and batch runs
Look at version management with Azure DevOps
You will need a basic PC/laptop; no prior knowledge of Microsoft Azure is required.