The correct answer is B because Databricks notebooks support real-time coauthoring on a single notebook, which is a better collaboration model than having two people work in separate Git branches on the same notebook content. Databricks’ notebook environment is designed for collaborative development, and the certification also expects you to know notebook capabilities in the workspace. databricks

Option-by-option explanation

• A: Databricks Notebooks support automatic change-tracking and versioning — Incorrect. Databricks notebooks do have version-related capabilities, but this option does not address the better collaboration method the question is asking about. The key improvement for simultaneous work is live collaboration, not just change history. docs.databricks

• B: Databricks Notebooks support real-time coauthoring on a single notebook — Correct. This directly supports pair programming or joint editing on the same notebook at the same time, which is the better alternative the senior engineer is referring to. databricks

• C: Databricks Notebooks support commenting and notification comments — Incorrect. Comments can help with review and discussion, but they do not let two engineers actively edit the same notebook together in real time. docs.databricks

• D: Databricks Notebooks support the use of multiple languages in the same notebook — Incorrect. Multi-language support is a useful notebook feature, but it is unrelated to collaboration between two engineers. docs.dataforgelabs

• E: Databricks Notebooks support the creation of interactive data visualizations — Incorrect. Visualizations are helpful for analysis and exploration, but they do not solve the collaboration problem described in the question. databricks

Answer

B is the best choice. Databricks notebooks support real-time coauthoring on a single notebook, making them a better collaboration tool than separate branches for simultaneous editing. docs.databricks