Answer: None of these changes will need to be made

**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

Author: Keng Suppaseth