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You have an Azure Databticks workspace that contains an all-purpose compute cluster named Cluster1. Cluser1 is used for
interactive development.
You need to configure Cluster1 to meet the following requirements:
• Automatically add and remove worker nodes based on workload demand
• Automatically shut down when the cluster has been idle for a specific period.
What should you configure for each requirement? To answer, drag the appropriate options to the correct requirements. Each option may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content
NOTE: Each correct selection is worth one point.
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Answer:
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Explanation
Two separate cluster settings address the two requirements: Autoscaling handles the first requirement — dynamically adding workers when the workload is heavy and removing them when it lightens. You set a minimum and maximum node count, and Databricks adjusts the cluster size between those bounds based on task queue depth. Auto-termination handles the second — the cluster shuts itself down after a configurable idle period (e.g., 30 minutes with no active queries), preventing wasted spend on a development cluster left running overnight. These two settings are independent and complementary: autoscaling manages horizontal elasticity during active use, while auto-termination manages complete shutdown during inactivity. Both are configured in the cluster creation UI under the Compute section. [Reference: https://learn.microsoft.com/en-us/azure/databricks/compute/configure#autoscaling, , ]
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You have an Azure Databricks workspace named Workspace1. You create a compute cluster named Cluser1 that will be used to ingest data.
You need to install the required libraries on Cluster 1. The solution must use Unity Catalog for access control. What should you do?
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B
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Explanation
The correct answer is B. The %pip install command (or pip3 in a terminal context) creates an isolated, per-session library environment in notebooks, which is the Unity Catalog-compatible approach. Unity Catalog workspaces require cluster access mode set to 'Shared' or 'Single User,' and %pip installs work seamlessly within those modes without requiring cluster restarts. Option A (custom dependency script) introduces extra maintenance work for every environment change — exactly what the question says to avoid. Option C installs libraries at the cluster level and requires a manual restart, which disrupts other users sharing the cluster and bypasses the per-notebook isolation model that Unity Catalog recommends. Option D uploads libraries to the Workspace file system (legacy DBFS approach), which is being deprecated in favour of Unity Catalog Volumes for library storage. [Reference: https://learn.microsoft.com/en-us/azure/databricks/libraries/notebooks-python-libraries, , ]
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You have an Azure Databricks workspace that is enabled for Unity Catalog.
You need to ensure that data lineage is captured and can be reviewed for tables accessed by Databricks notebooks and jobs. The solution must minimize administrative effort.
Which compute configuration should you use to capture the data lineage, and what should you use to review the data lineage? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
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Answer:
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Explanation
Data lineage in Unity Catalog is captured automatically — but only when jobs and notebooks run on clusters that are Unity Catalog-aware. Specifically, clusters must use 'Shared' or 'Single User' access mode. Clusters set to 'No Isolation Shared' or legacy 'High Concurrency' mode do not emit lineage events to the Unity Catalog lineage service. No instrumentation, logging code, or external tools are required. The lineage service operates transparently, intercepting read and write operations at the Spark plan level and recording the table-to-table and column-to-column relationships. To review captured lineage, open Catalog Explorer, navigate to the table, and select the Lineage tab. This shows the upstream sources that populate the table and the downstream consumers that read from it — all as an interactive graph, with no additional tooling needed. This built-in visibility is one of the core governance benefits Unity Catalog provides. [Reference: https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/data-lineage, , ]
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Find answers to the most common questions about the Microsoft DP-750 exam, including what it is, how to prepare, and how it can boost your career.
The Microsoft DP-750 certification is a globally-acknowledged credential that is awarded to candidates who pass this certification exam by obtaining the required passing score. This credential attests and validates the candidates' knowledge and hands-on skills in domains covered in the Microsoft DP-750 certification syllabus. The Microsoft DP-750 certified professionals with their verified proficiency and expertise are trusted and welcomed by hiring managers all over the world to perform leading roles in organizations. The success in Microsoft DP-750 certification exam can be ensured only with a combination of clear knowledge on all exam domains and securing the required practical training. Like any other credential, Microsoft DP-750 certification may require periodic renewal to stay current with new innovations in the concerned domains.