What you'll learn:
- Learn how to construct ELT solutions using Azure Data Factory and SQL Server.
- Implement various ELT solutions using Mapping Data Flows, Copy Activities, and Stored Procedures.
- Develop the skills to build and troubleshoot Azure Data Factory pipelines with confidence.
- Enhance pipeline reliability by mastering the use of parameters to optimize your data workflows.
- Learn efficient methods for storing and structuring data using Azure Storage services.
- Understand the distinctive roles played by Azure Data Factory, Data Storage, SQL Server, and Data Bricks in the creation of an ELT solution.
Use Azure data factory to automate data engineering tasks. This is a great course to introduce yourself to Azure Data Factory’s capabilities. We’ll look at the data factory from a data engineer perspective.
Through examples we’ll work side by side to create an Extract Transform and Load process to ingest movie rating data.
We are going to explore two different ways to transform your data.
The first is by using Azure Data Mapping flows. These are great no-code ways to do ETL.
Lastly, we’ll look at how you can create pipelines to use your knowledge of SQL and stored procedures.
What you’ll like about this course is that once you learn one way to transform the data, you can use that knowledge to learn about the other methods. So, if you’re a SQL expert but soft on python, you can learn the SQL way before trying another mapping method. In the end you come out learning and appreciating alternative methods to ingesting, transforming, and storing data.
Keep in mind this is more of "work with me" than "me talking to you" style of course. There are sections where I will start out lecturing about a concept, but I'd say during 80% of the course I'm working the tools, and I highly encourage you to work them along side me. Pause, rewind, and build it with me!
Also, don't be afraid to ask questions, I will answer them. :)
