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Microsoft DP-600 Exam Overview:
| Certification Vendor: | Microsoft |
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| Exam Name: | Implementing Analytics Solutions Using Microsoft Fabric |
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| Exam Number: | DP-600 |
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| Certificate Validity Period: | 2 years |
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| Exam Price: | USD 165 |
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| Available Languages: | Japanese, Spanish, Portuguese (Brazil), German, French, Chinese (Simplified), English |
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| Exam Format: | Case study, Multiple choice, Scenario-based |
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| Exam Duration: | 100 minutes |
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| Real Exam Qty: | 40–60 |
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| Passing Score: | 700 / 1000 |
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| Recommended Training: | Microsoft Learn: DP-600 Learning Path |
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| Exam Registration: | Microsoft Certification Exam Registration |
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| Sample Questions: | Microsoft DP-600 Sample Questions |
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| Exam Way: | Online proctored or onsite at authorized test centers |
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| Pre Condition: | No mandatory prerequisites; recommended experience with data modeling, SQL, DAX, and Microsoft Fabric components |
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| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-600 |
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| Topic | Details |
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| 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.
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| 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.
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| 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 (Q78-Q83):
NEW QUESTION # 78
You have a Fabric warehouse that contains a table named Staging.Sales. Staging.Sales contains the following columns.

You need to write a T-SQL query that will return data for the year 2023 that displays ProductID and ProductName arxl has a summarized Amount that is higher than 10,000. Which query should you use?
Answer: C
Explanation:
The correct query to use in order to return data for the year 2023 that displays ProductID, ProductName, and has a sum marized Amount greater than 10,000 is Option B. The reason is that it uses the GROUP BY clause to organize the data by ProductID and ProductName and then filters the result using the HAVING clause to only include groups where the sum of Amount is greater t han 10,000. Additionally, the DATEPART (YEAR, SaleDate) = ' 2023 ' part of the HAVING clause ensures that only records from the year 2023 are included. References = For more information, please visit the official documentation on T-SQL queries and the GROUP BY clause at T-SQL GROUP BY .
NEW QUESTION # 79
You have a Fabric tenant that contains a workspace named Workspace_DEV. Workspace_DEV contains the semantic models shown in the following table.

Workspace_DEV contains the dataflows shown in the following table.


Answer:
Explanation:

Explanation:

DF1 will be deployed to Workspace_TEST: Yes
Data from Model1 will be deployed to Workspace_TEST: No
The scheduled refresh policy for Model1 will be deployed to Workspace_TEST: No DF1 is a Dataflow Gen1 with a configured scheduled refresh policy, so it will be deployed to Workspace_TEST.
Data from Model1 will not be deployed as Model1 ' s scheduled refresh policy is not configured, indicating it is not set up for deployment.
The scheduled refresh policy for Model1 will not be deployed since it is listed as " Not configured. "
NEW QUESTION # 80
You have the source data model shown in the following exhibit.

The primary keys of the tables are indicated by a key symbol beside the columns involved in each key.
You need to create a dimensional data model that will enable the analysis of order items by date, product, and customer.
What should you include in the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:

* The relationship between OrderItem and Product must be based on: Both the CompanyID and the ProductID columns
* The Company entity must be: Denormalized into the Customer and Product entities In a dimensional model, the relationships are typically based on foreign key constraints between the fact table (OrderItem) and dimension tables (Product, Customer, Date). Since CompanyID is present in both the OrderItem and Product tables, it acts as a foreign key in the relationship. Similarly, ProductID is a foreign key that relates these two tables. To enable analysis by date, product, and customer, the Company entity would need to be denormalized into the Customer and Product entities to ensure that the relevant company information is available within those dimensions for querying and reporting purposes.
References =
* Dimensional modeling
* Star schema design
NEW QUESTION # 81
You have a Fabric tenant that contains a lakehouse.
You plan to query sales data files by using the SQL endpoint. The files will be in an Amazon Simple Storage Service (Amazon S3) storage bucket.
You need to recommend which file format to use and where to create a shortcut.
Which two actions should you include in the recommendation? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.
- A. Create a shortcut in the Files section.
- B. Use the Parquet format
- C. Use the delta format.
- D. Use the CSV format.
- E. Create a shortcut in the Tables section.
Answer: A,B
NEW QUESTION # 82
You have a Microsoft Power Bl semantic model.
You plan to implement calculation groups.
You need to create a calculation item that will change the context from the selected date to month-to-date (MTD).
How should you complete the DAX expression? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:

To create a calculation item that changes the context from the selected date to month-to-date (MTD), the appropriate DAX expression involves using the CALCULATE function to alter the filter context and the DATESMTD function to specify the month-to-date context.
The correct completion for the DAX expression would be:
In the first dropdown, select CALCULATE.
In the second dropdown, select SELECTEDMEASURE.
This would create a DAX expression in the form:
CALCULATE(
SELECTEDMEASURE(),
DATESMTD( ' Date ' [DateColumn])
)
NEW QUESTION # 83
......
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