Azure Data Factory for Beginners - Build Data Ingestion - Understanding the Pipeline Log and Related Tables

The video tutorial covers the pipeline log table used for auditing data ingestion, explaining its standalone nature and relationship with the batch run table. It details how to query these tables, interpret batch run statuses, and measure latency. The tutorial also discusses the pipeline log's role in tracing log files and its integration with Azure Data Factory.

What is the primary purpose of the pipeline log table?

What is the significance of the run ID in the pipeline log?

Explain the relationship between the pipeline log table and the batch run table.

What information is necessary to calculate the duration of a batch run?

Describe the different statuses a batch run can have.

What does the term 'latency' refer to in the context of batch runs?

How does the pipeline log indicate whether a run was successful or failed?