DP-700 Mock Exam | Hot DP-700 Questions

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Microsoft DP-700 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Implement and manage an analytics solution	30–35%	- Configure workspace settings 1. Configure domain workspace settings 2. Configure Spark workspace settings 3. Configure Dataflows Gen2 settings 4. Configure OneLake workspace settings 5. Configure Microsoft Fabric workspace settings - Manage data lifecycle and governance 1. Manage data access and security 2. Implement data governance with Microsoft Purview 3. Implement data retention and archiving - Manage data storage 1. Choose appropriate data stores 2. Create and manage OneLake shortcuts 3. Implement data mirroring
Topic 2: Ingest and transform data	30–35%	- Design and implement data loading patterns 1. Prepare data for dimensional models 2. Design streaming data loading patterns 3. Design full and incremental data loads - Ingest data 1. Ingest data using pipelines 2. Ingest data using Eventstreams 3. Ingest data using Dataflows Gen2 - Orchestrate data operations 1. Orchestrate with notebooks and pipelines 2. Use parameters and dynamic expressions 3. Implement schedules and triggers - Transform data 1. Transform data using KQL 2. Transform data using SQL 3. Clean, denormalize, and aggregate data 4. Transform data using PySpark
Topic 3: Monitor and optimize an analytics solution	30–35%	- Monitor analytics solutions 1. Monitor semantic model refreshes 2. Configure alerts and notifications 3. Monitor Fabric items and activities 4. Monitor data ingestion and transformation - Optimize performance 1. Optimize Lakehouse and data warehouse performance 2. Optimize pipelines and data flows 3. Optimize storage efficiency 4. Optimize Spark and query performance - Troubleshoot issues 1. Identify and resolve storage and query errors 2. Identify and resolve notebook and Spark errors 3. Identify and resolve pipeline errors 4. Identify and resolve Dataflow errors

Section

Weight

Objectives

Topic 1: Implement and manage an analytics solution

30–35%

- Configure workspace settings

1. Configure domain workspace settings
2. Configure Spark workspace settings
3. Configure Dataflows Gen2 settings
4. Configure OneLake workspace settings
5. Configure Microsoft Fabric workspace settings

- Manage data lifecycle and governance

1. Manage data access and security
2. Implement data governance with Microsoft Purview
3. Implement data retention and archiving

- Manage data storage

1. Choose appropriate data stores
2. Create and manage OneLake shortcuts
3. Implement data mirroring

Topic 2: Ingest and transform data

30–35%

- Design and implement data loading patterns

1. Prepare data for dimensional models
2. Design streaming data loading patterns
3. Design full and incremental data loads

- Ingest data

1. Ingest data using pipelines
2. Ingest data using Eventstreams
3. Ingest data using Dataflows Gen2

- Orchestrate data operations

1. Orchestrate with notebooks and pipelines
2. Use parameters and dynamic expressions
3. Implement schedules and triggers

- Transform data

1. Transform data using KQL
2. Transform data using SQL
3. Clean, denormalize, and aggregate data
4. Transform data using PySpark

Topic 3: Monitor and optimize an analytics solution

30–35%

- Monitor analytics solutions

1. Monitor semantic model refreshes
2. Configure alerts and notifications
3. Monitor Fabric items and activities
4. Monitor data ingestion and transformation

- Optimize performance

1. Optimize Lakehouse and data warehouse performance
2. Optimize pipelines and data flows
3. Optimize storage efficiency
4. Optimize Spark and query performance

- Troubleshoot issues

1. Identify and resolve storage and query errors
2. Identify and resolve notebook and Spark errors
3. Identify and resolve pipeline errors
4. Identify and resolve Dataflow errors

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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q103-Q108):

NEW QUESTION # 103
You have a Fabric workspace that contains a lakehouse and a notebook named Notebook1. Notebook1 reads data into a DataFrame from a table named Table1 and applies transformation logic. The data from the DataFrame is then written to a new Delta table named Table2 by using a merge operation.
You need to consolidate the underlying Parquet files in Table1.
Which command should you run?

A. VACUUM
B. CACHE
C. BROADCAST
D. OPTIMIZE

Answer: D

Explanation:
To consolidate the underlying Parquet files in Table1 and improve query performance by optimizing the data layout, you should use the OPTIMIZE command in Delta Lake. The OPTIMIZE command coalesces smaller files into larger ones and reorganizes the data for more efficient reads. This is particularly useful when working with large datasets in Delta tables, as it helps reduce the number of files and improves performance for subsequent queries or operations like MERGE.

NEW QUESTION # 104
You have three users named User1, User2, and User3.
You have the Fabric workspaces shown in the following table.

You have a security group named Group1 that contains User1 and User3.
The Fabric admin creates the domains shown in the following table.

User1 creates a new workspace named Workspace3.
You add Group1 to the default domain of Domain1.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 105
You have five Fabric workspaces.
You are monitoring the execution of items by using Monitoring hub.
You need to identify in which workspace a specific item runs.
Which column should you view in Monitoring hub?

A. Submitter
B. Job type
C. Item type
D. Start time
E. Activity name
F. Location
G. Capacity

Answer: F

Explanation:
To identify in which workspace a specific item runs in Monitoring hub, you should view the Location column. This column indicates the workspace where the item is executed. Since you have multiple workspaces and need to track the execution of items across them, the Location column will show you the exact workspace associated with each item or job execution.

NEW QUESTION # 106
You have a Fabric workspace that contains a warehouse named Warehouse1. Warehouse1 contains a table named Customer. Customer contains the following data.

Answer:

Explanation:

Explanation:

NEW QUESTION # 107
You need to ensure that the authors can see only their respective sales data.
How should you complete the statement? 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:

Explanation:

NEW QUESTION # 108
......

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