Databricks Certified Data Engineer - Associate

Explanation:

Delta Live Tables (DLT) is designed to be compatible with existing Databricks pipelines and provides flexibility in implementation. Let's analyze each option:

1. Option A (Correct): None of these changes will need to be made - This is correct because DLT supports:

   • Medallion architecture (bronze, silver, gold layers)
   • Both SQL and Python (or a mix)
   • Both batch and streaming processing
   • Existing pipeline patterns

2. Option B: The pipeline will need to stop using the medallion-based multi-hop architecture - Incorrect. DLT actually encourages and supports the medallion architecture with its built-in support for multi-hop data pipelines.

3. Option C: The pipeline will need to be written entirely in SQL - Incorrect. DLT supports both SQL and Python, allowing you to use either language or a combination of both.

4. Option D: The pipeline will need to use a batch source in place of a streaming source - Incorrect. DLT supports both batch and streaming processing, and you can use streaming sources in DLT pipelines.

5. Option E: The pipeline will need to be written entirely in Python - Incorrect. As mentioned, DLT supports both SQL and Python.

Key Points:

• DLT is designed to simplify pipeline development and maintenance
• It provides built-in quality controls, monitoring, and error handling
• You can migrate existing pipelines to DLT without major architectural changes
• DLT supports the medallion architecture, mixed language usage, and both batch/streaming processing modes