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Microsoft DP-700 Exam Syllabus Topics:
Topic
Details
Topic 1
Topic 2
Topic 3
Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q14-Q19):
NEW QUESTION # 14
You have a Fabric workspace that contains an eventstream named EventStream1.
You discover that an EventStream1 transformation fails.
You need to find the following error information:
The error details, including the occurrence time
The total number of errors
What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 15
You have a Fabric workspace that contains a warehouse named DW1. DW1 contains the following tables and columns.
You need to create an output that presents the summarized values of all the order quantities by year and product. The results must include a summary of the order quantities at the year level for all the products.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 16
You have a Fabric workspace named Workspace1 that contains a lakehouse named Lakehouse1. Lakehouse1 contains the following tables:
Orders
Customer
Employee
The Employee table contains Personally Identifiable Information (PII).
A data engineer is building a workflow that requires writing data to the Customer table, however, the user does NOT have the elevated permissions required to view the contents of the Employee table.
You need to ensure that the data engineer can write data to the Customer table without reading data from the Employee table.
Which three actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: D,E,F
Explanation:
To meet the requirements of ensuring that the data engineer can write data to the Customer table without reading data from the Employee table (which contains Personally Identifiable Information, or PII), you can implement the following steps:
Share Lakehouse1 with the data engineer.
By sharing Lakehouse1 with the data engineer, you provide the necessary access to the data within the lakehouse. However, this access should be controlled through roles and permissions, which will allow writing to the Customer table but prevent reading from the Employee table.
Assign the data engineer the Contributor role for Workspace1.
Assigning the Contributor role for Workspace1 grants the data engineer the ability to perform actions such as writing to tables (e.g., the Customer table) within the workspace. This role typically allows users to modify and manage data without necessarily granting them access to view all data (e.g., PII data in the Employee table).
Migrate the Employee table from Lakehouse1 to Lakehouse2.
To prevent the data engineer from accessing the Employee table (which contains PII), you can migrate the Employee table to a separate lakehouse (Lakehouse2) or workspace (Workspace2). This separation of sensitive data ensures that the data engineer's access is restricted to the Customer table in Lakehouse1, while the Employee table can be managed separately and protected under different access controls.
NEW QUESTION # 17
You have a Fabric workspace that contains a lakehouse named Lakehouse1. Lakehouse1 contains a Delta table named Table1.
You analyze Table1 and discover that Table1 contains 2,000 Parquet files of 1 MB each.
You need to minimize how long it takes to query Table1.
What should you do?
Answer: A
Explanation:
Problem Overview:
Table1 has 2,000 small Parquet files (1 MB each).
Query performance suffers when the table contains numerous small files because the query engine must process each file individually, leading to significant overhead.
Solution:
To improve performance, file compaction is necessary to reduce the number of small files and create larger, optimized files.
Commands and Their Roles:
OPTIMIZE Command:
- Compacts small Parquet files into larger files to improve query performance.
- It supports optional features like V-Order, which organizes data for efficient scanning.
VACUUM Command:
- Removes old, unreferenced data files and metadata from the Delta table.
- Running VACUUM after OPTIMIZE ensures unnecessary files are cleaned up, reducing storage overhead and improving performance.
NEW QUESTION # 18
You have a Fabric eventhouse that contains a KQL database. The database contains a table named TaxiData. The following is a sample of the data in TaxiData.
You need to build two KQL queries. The solution must meet the following requirements:
How should you complete each query? To answer, drag the appropriate values the correct targets. Each value 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.
Answer:
Explanation:
NEW QUESTION # 19
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