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NEW QUESTION: 1

A. Option A
B. Option D
C. Option B
D. Option C
Answer: A

NEW QUESTION: 2
You have a technician computer named Computer1 and a server named Server1.
You plan to deploy several images to computers on the network. The planned installation will include multiple language packs.
You create a folder on Server1 and share the folder as Share1.
You need to configure Share1 as a distribution share from Windows System Image Manager (Windows SIM).
What should you do first?
A. Copy the Windows Assessment and Deployment Kit (Windows ADK) to Share1.
B. Copy the Windows 8 installation media to Share1.
C. Create a folder named Install in Share1.
D. Create a folder named Packages in Share1.
Answer: D
Explanation:
To import a package - Select and open a distribution share. For more information, see Open a Distribution Share. - On the Tools menu, select Import Package(s).The Select Package(s) to Import window opens.
- Navigate to the file or folder, select the file or folder, and then click Open or Open Folder.Windows SIM adds the selected package to the distribution share folder. The newly added package is displayed under the Packages node in the Distribution Share pane.
Reference: Import a Package to a Distribution Share

NEW QUESTION: 3
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 scenario, 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, Spark, Scala, and SQL
* 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 Databrick clusters for the workloads.
Solution: You create a High Concurrency cluster for each data scientist, a High Concurrency cluster for the data engineers, and a Standard cluster for the jobs.
Does this meet the goal?
A. Yes
B. No
Answer: B
Explanation:
Explanation
No need for a High Concurrency cluster for each data scientist.
Standard clusters are recommended for a single user. Standard can run workloads developed in any language:
Python, R, Scala, and SQL.
A high concurrency cluster is a managed cloud resource. The key benefits of high concurrency clusters are that they provide Apache Spark-native fine-grained sharing for maximum resource utilization and minimum query latencies.
References:
https://docs.azuredatabricks.net/clusters/configure.html