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Microsoft DP-600 Exam Syllabus Topics:

Section	Objectives
Topic 1: Get data into Microsoft Fabric	- Data ingestion and integration 1. Dataflows Gen2 2. Data pipelines in Microsoft Fabric
Topic 2: Manage and secure Microsoft Fabric	- Governance and administration 1. Security and access control 2. Monitoring and compliance
Topic 3: Implement data engineering solutions	- Lakehouse architecture 1. Delta tables management 2. Spark notebooks in Fabric
Topic 4: Real-time analytics	- Streaming and event processing 1. Kusto Query Language (KQL) analytics 2. Eventstreams in Microsoft Fabric
Topic 5: Implement analytics solutions	- Data warehousing and modeling 1. Fabric Warehouse 2. Semantic models for Power BI

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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q154-Q159):

NEW QUESTION # 154
You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1 contains a table named Tablet.
You are creating a new data pipeline.
You plan to copy external data to Table1. The schema of the external data changes regularly.
You need the copy operation to meet the following requirements:
- Replace Table1 with the schema of the external data.
- Replace all the data in Table1 with the rows in the external data.
You add a Copy data activity to the pipeline.
What should you do for the Copy data activity?

A. From the Source tab, add additional columns.
B. From the Destination tab, set Table action to Overwrite.
C. From the Settings tab, select Enable staging.
D. From the Source tab, select Enable partition discovery.
E. From the Source tab, select Recursively.

Answer: B

Explanation:
Enable "Truncate table" option: This option truncates the target table before copying data, ensuring that all existing data is replaced with the new data from the external source.

NEW QUESTION # 155
Which workspace rote assignments should you recommend for ResearchReviewersGroupl and ResearchReviewersGroupZ? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

NEW QUESTION # 156
You have a Fabric tenant that contains two workspaces named Workspace1 and Workspace2.
Workspace1 contains a lakehouse named Lakehouse1. Workspace2 contains a lakehouse named Lakehouse2. Lakehouse1 contains a table named dbo.Sales. Lakehouse2 contains a table named dbo.Customers.
You need to ensure that you can write queries that reference both dbo.Sales and dbo.Customers in the same SQL query without making additional copies of the tables.
What should you use?

A. a dataflow
B. a managed table
C. a shortcut
D. a view

Answer: C

NEW QUESTION # 157
You have a Fabric notebook that has the Python code and output shown in the following exhibit.

Which type of analytics are you performing?

A. descriptive
B. prescriptive
C. predictive
D. diagnostic

Answer: A

Explanation:
The Python code and output shown in the exhibit display a histogram, which is a representation of the distribution of data. This kind of analysis is descriptive analytics, which is used to describe or summarize the features of a dataset. Descriptive analytics answers the question of "what has happened" by providing insight into past data through tools such as mean, median, mode, standard deviation, and graphical representations like histograms.
References: Descriptive analytics and the use of histograms as a way to visualize data distribution are basic concepts in data analysis, often covered in introductory analytics and Python programming resources.

NEW QUESTION # 158
You have a Fabric workspace named Workspace1 that contains a lakehouse named Lakehouse1 and a user named User1.
You need to ensure that User1 can read all the data in Lakehouse1. The solution must follow the principle of least privilege.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Assign the Contributor role to User1.
B. Select Read all Apache Spark.
C. Assign the Viewer role to User1.
D. Assign the Member role to User1.
E. Share Lakehouse1 by using item permissions.

Answer: B,E

Explanation:
To ensure a user has read access to all data in a Microsoft Fabric lakehouse while following the Principle of Least Privilege (PoLP), you should use Item-level sharing rather than assigning a workspace role.
Workspace roles like Admin, Member, or Contributor grant broad permissions across all items in a workspace, which is often unnecessary for a data consumer.
Implementation Steps
1. Avoid Workspace Roles: Do not add the user as an Admin, Member, or Contributor to the workspace. This prevents them from managing items or writing data.
[D] 2. Use the Share Feature: Navigate to the specific lakehouse and select Share.
3. Configure Granular Permissions: In the sharing dialog, select the following based on the user's technical needs:
3a. Read all SQL endpoint data (ReadData): Required if the user will query data using T-SQL, SQL Server Management Studio (SSMS), or Power BI reports.
[B] 3b. Read all Apache Spark (ReadAll): Required if the user needs to read data via Spark notebooks, OneLake APIs, or the Lakehouse explorer.
3c.Build reports on the default semantic model (Build): Necessary if they need to create new Power BI reports using the lakehouse's data.
Reference:
https://data-mozart.com/understanding-data-access-options-in-microsoft-fabric/

NEW QUESTION # 159
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