Databricks Certified Data Engineer - Associate

Explanation

When implementing an ELT pipeline with Delta Live Tables (DLT) that involves multiple notebooks that need to be executed in a specific order, the correct approach is:

B. They need to create a Delta Live Tables pipeline from the Jobs page.

Why this is correct:

1. Delta Live Tables pipelines are created from the Jobs page - This is where you configure and manage DLT pipelines in Databricks.
2. DLT pipelines manage execution order - When you create a DLT pipeline, you can specify the notebooks and their execution order, which is exactly what the data engineer needs.
3. DLT handles orchestration - DLT automatically manages dependencies between notebooks and ensures they run in the correct order.

Why the other options are incorrect:

• A. They need to create a Delta Live Tables pipeline from the Data page. ❌ Incorrect - DLT pipelines are not created from the Data page.
• C. They need to create a Delta Live tables pipeline from the Compute page. ❌ Incorrect - DLT pipelines are not created from the Compute page.
• D. They need to refactor their notebook to use Python and the dlt library. ❌ Not necessarily required - While DLT supports Python with the dlt library, you can also use SQL. The key requirement is creating the pipeline from the Jobs page.
• E. They need to refactor their notebook to use SQL and CREATE LIVE TABLE keyword. ❌ Not necessarily required - While SQL with CREATE LIVE TABLE is one approach, Python with the dlt decorator is also valid. The fundamental requirement is creating the DLT pipeline from the Jobs page.

Key Takeaway:

Delta Live Tables pipelines are created and managed through the Jobs page in Databricks, where you can configure notebook dependencies and execution order for your ELT workflows.