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Microsoft DP-600 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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.
Topic 3	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.

Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q14-Q19):

NEW QUESTION # 14
You have a Fabric workspace named Workspacel that contains a lakehouse named Lakehousel. Lakehousel contains a table named Tablel. Table 1 contains the following data.

You need to perform the following actions:
* Load the data from Table! into a star schema.
* Create a product dimension table named DimProduct and a fact table named FactSales.
Which three columns should you include in DimProduct?

A. ProductName, SalesAmount, andTransactionlD
B. ProductColor, ProductID, and ProductName.
C. ProductID, ProductName, and SalesAmount
D. Date, ProductID, andTransactionlD.

Answer: B

NEW QUESTION # 15
Hotspot Question
You have a Fabric tenant that contains a warehouse named Warehouse1. Warehouse1 contains a fact table named FactSales that has one billion rows.
You run the following T-SQL statement.
CREATE TABLE test.FactSales AS CLONE OF dbo.FactSales;
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:

Explanation:
https://learn.microsoft.com/en-us/sql/t-sql/statements/create-table-as-clone-of-transact- sql?view=fabric&preserve-view=true Creates a new table as a zero-copy clone of another table in Warehouse in Microsoft Fabric. Only the metadata of the table is copied. The underlying data of the table, stored as parquet files, is not copied.
https://learn.microsoft.com/en-us/fabric/data-warehouse/clone-table
Separate and independent
Upon creation, a table clone is an independent and separate copy of the data from its source.
Any changes made through DML or DDL on the source of the clone table are not reflected in the clone table.Similarly, any changes made through DDL or DML on the table clone are not reflected on the source of the clone table.

NEW QUESTION # 16
You have a Fabric tenant that contains a lakehouse named lakehouse1. Lakehouse1 contains a table named Table1.
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 Recursively
E. From the Source tab, select Enable partition discovery

Answer: B

Explanation:
For the Copy data activity, from the Destination tab, setting Table action to Overwrite (B) will ensure that Table1 is replaced with the schema and rows of the external data, meeting the requirements of replacing both the schema and data of the destination table. References = Information about Copy data activity and table actions in Azure Data Factory, which can be applied to data pipelines in Fabric, is available in the Azure Data Factory documentation.

NEW QUESTION # 17
You have a Microsoft Power Bl project that contains a file named definition.pbir. definition.pbir contains the following JSON.

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:

Explanation:

We are analyzing the JSON for definition.pbir in a Power BI Project:
{
"version": "1.0",
"datasetReference": {
"byPath": {
"path": "../Sales.Dataset"
},
"byConnection": null
}
}
Statement 1:
"definition.pbir is in the PBIR-Legacy format."
No # The legacy PBIR format references datasets by byConnection (pointing to the Power BI service).
Here, it uses byPath, which is the new project format, not legacy.
Statement 2:
"The semantic model referenced by definition.pbir is located in the Power BI service." No # The JSON shows byPath: "../Sales.Dataset", meaning the semantic model is referenced locally within the project folder (Sales.Dataset), not in the Power BI service.
Statement 3:
"When the related report is opened, Power BI Desktop will open the semantic model in full edit mode." Yes # Since the semantic model is referenced by path (local PBIP project files), Power BI Desktop will open the model in full edit mode. If it had been byConnection, it would open in live connect mode to the service instead.
Final Answer:
PBIR-Legacy format # No
Semantic model in Power BI service # No
Opens in full edit mode # Yes
References:
Power BI Project (PBIP) structure
PBIR formats: byPath vs byConnection

NEW QUESTION # 18
Hotspot Question
You have a data warehouse that contains a table named Stage.Customers. Stage.Customers contains all the customer record updates from a customer relationship management (CRM) system. There can be multiple updates per customer.
You need to write a T-SQL query that will return the customer ID, name. postal code, and the last updated time of the most recent row for each customer ID.
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 # 19
......

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