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Microsoft DP-600 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Prepare data: This section of the exam measures the skills of engineers and covers essential data preparation tasks. It includes establishing data connections and discovering sources through tools like the OneLake data hub and the real-time hub. Candidates must demonstrate knowledge of selecting the appropriate storage type—lakehouse, warehouse, or eventhouse—depending on the use case. It also includes implementing OneLake integrations with Eventhouse and semantic models. The transformation part involves creating views, stored procedures, and functions, as well as enriching, merging, denormalizing, and aggregating data. Engineers are also expected to handle data quality issues like duplicates, missing values, and nulls, along with converting data types and filtering. Furthermore, querying and analyzing data using tools like SQL, KQL, and the Visual Query Editor is tested in this domain.
Topic 2
  • Implement and manage semantic models: This section of the exam measures the skills of architects and focuses on designing and optimizing semantic models to support enterprise-scale analytics. It evaluates understanding of storage modes and implementing star schemas and complex relationships, such as bridge tables and many-to-many joins. Architects must write DAX-based calculations using variables, iterators, and filtering techniques. The use of calculation groups, dynamic format strings, and field parameters is included. The section also includes configuring large semantic models and designing composite models. For optimization, candidates are expected to improve report visual and DAX performance, configure Direct Lake behaviors, and implement incremental refresh strategies effectively.
Topic 3
  • Maintain a data analytics solution: This section of the exam measures the skills of administrators and covers tasks related to enforcing security and managing the Power BI environment. It involves setting up access controls at both workspace and item levels, ensuring appropriate permissions for users and groups. Row-level, column-level, object-level, and file-level access controls are also included, alongside the application of sensitivity labels to classify data securely. This section also tests the ability to endorse Power BI items for organizational use and oversee the complete development lifecycle of analytics assets by configuring version control, managing Power BI Desktop projects, setting up deployment pipelines, assessing downstream impacts from various data assets, and handling semantic model deployments using XMLA endpoint. Reusable asset management is also a part of this domain.

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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q111-Q116):

NEW QUESTION # 111
You have a Fabric tenant that contains lakehouse named Lakehouse1. Lakehouse1 contains a Delta table with eight columns. You receive new data that contains the same eight columns and two additional columns.
You create a Spark DataFrame and assign the DataFrame to a variable named df. The DataFrame contains the new data. You need to add the new data to the Delta table to meet the following requirements:
* Keep all the existing rows.
* Ensure that all the new data is added to the table.
How should you complete the code? To answer, select the appropriate options in the answer area.

Answer:

Explanation:

Explanation:

o add new data to the Delta table while meeting the specified requirements:
You should use the append mode to ensure that all new data is added to the table without affecting the existing rows.
You should set the mergeSchema option to true to allow the schema of the Delta table to be updated with the new columns found in the DataFrame.
The completed code would look like this:
df.write.format( " delta " ).mode( " append " )
option( " mergeSchema " , " true " )
saveAsTable( " Lakehouse1.TableName " )


NEW QUESTION # 112
You have a Fabric tenant that contains a data warehouse.
You need to load rows into a large Type 2 slowly changing dimension (SCD). The solution must minimize resource usage.
Which T-SQL statement should you use?

Answer: B

Explanation:
Merg allow you to do :
- Insert new records for changes.
- Update existing records to mark them as historical.
- Maintain the history of changes efficiently.


NEW QUESTION # 113
You have a Fabric tenant that contains two lakehouses.
You are building a dataflow that will combine data from the lakehouses. The applied steps from one of the queries in the dataflow is shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic. NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 114
You have a Fabric workspace named Workspace1 and an Azure Data Lake Storage Gen2 account named storage " !. Workspace1 contains a lakehouse named Lakehouse1.
You need to create a shortcut to storage! in Lakehouse1.
Which connection and endpoint should you specify? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

When creating a shortcut to an Azure Data Lake Storage Gen2 account in a lakehouse, you should use the abfss (Azure Blob File System Secure) connection string and the dfs (Data Lake File System) endpoint. The abfss is used for secure access to Azure Data Lake Storage, and the dfs endpoint indicates that the Data Lake Storage Gen2 capabilities are to be used.


NEW QUESTION # 115
You have a Fabric tenant that contains a workspace named Workspace1 and a user named User1. Workspace1 contains a warehouse named DW1.
You share DW1 with User1 and assign User1 the default permissions for DW1.
What can User1 do?

Answer: A

Explanation:
Comprehensive Detailed Explanation
Step 1: Default permissions when sharing a warehouse in Fabric
When you share a Fabric warehouse (DW1) with a user and assign them default permissions, the user:
Gets Build permission by default.
Build permission allows the user to:
Use the default dataset automatically created for the warehouse.
Build reports and dashboards against that dataset.
It does not grant direct query permissions to the underlying tables or files.
Step 2: Analyze the options
A). Build reports by using the default dataset. #
Correct. Sharing a warehouse gives Build permission on the warehouse's default dataset.
User1 can create Power BI reports but cannot directly query the warehouse via SQL.
B). Read the underlying Parquet files from OneLake.
Incorrect. Access to underlying OneLake files requires Direct Lake storage access or shortcut permissions, not provided by default sharing.
C). Connect to DW1 via the TDS endpoint.
Incorrect. The TDS endpoint is supported by semantic models, not warehouses.
D). Read data from the tables in DW1.
Incorrect. Default permissions do not allow table-level SQL access. They allow using the dataset for reporting.
Step 3: Correct Answer
The only capability User1 has by default is:
A). Build reports by using the default dataset.
References
Fabric warehouses - permissions
Build permission in Power BI


NEW QUESTION # 116
......

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