Developing Testing Processes for Data Pipelines

This section was covered in To summarize, you explored the process of creating data pipelines using ADF or Synapse. You also learned how to design and construct these pipelines to orchestrate data movement and transformations effectively. Additionally, you delved into triggering these pipelines and monitoring their executions to ensure they run as expected.

You also integrated low-code solutions with code execution by learning how to call a Spark Notebook from within a pipeline. This capability will allow you to seamlessly blend the simplicity of low-code approaches with the power and flexibility of code execution, enabling more versatile and efficient data workflows. By learning how to incorporate Spark Notebooks into your pipelines, you can enhance your data processing capabilities and streamline your data engineering tasks.

Note

This section primarily focuses on the Create tests for data pipelines concept of the DP-203: Data...