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Microsoft DP-750 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Secure and govern Unity Catalog objects | 15β20% | - Implement data governance and security
|
| Prepare and process data | 30β35% | - Ingest and transform data
|
| Set up and configure an Azure Databricks environment | 15β20% | - Select and configure compute resources
|
| Deploy and maintain data pipelines and workloads | 30β35% | - Build and orchestrate pipelines
|
Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:
You have an Azure Databricks workspace that contains the objects shown in the following table.
Name | Type
Catalog1 | Catalog
Schema1 | Schema
Sales1 | Table
Notebook1 | Notebook
Space1 | AI/BI Genie space
Users often use the following words to refer to a sale: transaction, event, order, and invoice.
You need to create a knowledge store. The solution must ensure that when the users use any of the words in Space1, Genie queries the Sales1 table. Any other Genie spaces must remain unaffected.
To which object should you add the instructions?
- A. Space1
- B. Notebook1
- C. Sales1
- D. Schema1
Correct Answer: A π³οΈ
Explanation: Only visible for VCEDumps members. You can sign-up / login (it's free).
You have an Azure Databricks workspace that is enabled for Unity Catalog.
You plan to create a job in Lakeflow Jobs named Job1 that:
* Ingests data from cloud storage
* Runs two independent transformation tasks
The transformation tasks must run only after the ingestion completes and must run in parallel.
You need to design the task logic for Job1.
What should you configure?
- A. One ingestion task with two parallel downstream transformation tasks
- B. independent tasks with no defined dependencies
- C. two ingestion tasks, each followed by a transformation task
- D. a single task that performs ingestion and transformations sequentially
Correct Answer: A π³οΈ
Explanation: Only visible for VCEDumps members. You can sign-up / login (it's free).
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a managed Delta table named Table1.
Table1 stores customer profile data.
Business users must analyze how customer profile records change over time. They must also be able to query earlier versions of the table.
You need to implement a solution that:
* Maintains persistent historical versions of customer profile records for long-term analysis.
* Allows users to query earlier versions of the Delta table.
* Minimizes maintenance effort.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
To record historical changes: Implement a Type 2 slowly changing dimension (SCD).
To support temporal analysis: Use Delta Lake time travel.
A Type 2 slowly changing dimension preserves customer-profile history by inserting a new record whenever a tracked attribute changes instead of overwriting the existing record. Effective dates, expiration dates, version values, or current-record indicators can identify which version applied during a particular period. This provides persistent business history for long-term analysis. Delta Lake time travel supports temporal analysis of the physical table by allowing users to query an earlier version with VERSION AS OF or TIMESTAMP AS OF. Time travel is useful for auditing and reproducing previous results, but its availability depends on retained Delta log entries and data files. Therefore, it should not replace a Type 2 SCD for permanent customer history. Together, the two features satisfy the historical-record and earlier-version requirements.
You have an Azure Databricks workspace that is enabled for Unity Catalog.
You have a complex job named Job1 that contains eight tasks. Job1 takes multiple hours to complete.
During the last job run, the final task fails due to a transient issue.
You need to retry the last task without rerunning tasks that have already completed.
What should you do?
- A. Disable and reenable the job schedule.
- B. Update the job parameters.
- C. Restart Job1.
- D. Repair the current job run.
Correct Answer: D π³οΈ
Explanation: Only visible for VCEDumps members. You can sign-up / login (it's free).
You have an Azure Databricks workspace named Workspace! that uses a Git repository. The repository contains a Databricks notebook named Notebook1.
From the main branch, you create a feature branch named Branch! and commit changes to Notebooks Another user commits changes to Notebook1 in main.
When you attempt to merge Branch! into main, the merge fails due to conflicts.
You need to merge Branch! into the main branch. The solution must ensure that Notebook1 includes all the changes from both the branches.
What should you do?
- A. Apply the main branch changes to Branch! and resolve the conflicts.
- B. Apply the changes directly to the main branch.
- C. From Workspace1, clone Branch! as a new repository.
- D. From Workspace1, clone the mam branch as a new repository.
Correct Answer: A π³οΈ
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