Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might h

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You plan to create an Azure Databricks workspace that has a tiered structure. The workspace will contain the following three workloads:

• A workload for data engineers who will use Python and SQL.
• A workload for jobs that will run notebooks that use Python, Scala,

and SOL.

• A workload that data scientists will use to perform ad hoc analysis

in Scala and R. The enterprise architecture team at your company identifies the following standards for Databricks environments:

• The data engineers must share a cluster.
• The job cluster will be managed by using a request process whereby

data scientists and data engineers provide packaged notebooks for deployment to the cluster.

• All the data scientists must be assigned their own cluster that

terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists. You need to create the Databricks clusters for the workloads. Solution: You create a Standard cluster for each data scientist, a High Concurrency cluster for the data engineers, and a High Concurrency cluster for the jobs. Does this meet the goal?