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Microsoft DP-600 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q37-Q42):

NEW QUESTION # 37
You have a Fabric workspace that contains a warehouse named Warehouse!. Warehousel contains the following data.

You need to create a T-SQL statement that will denormalize the tables and include the ContractType and StartDate attributes in the results. The solution must meet the following requirements:
* Include attributes from matching rows in the Contract table.
* Ensure that all the rows from the Employee table are preserved.
* Return the total number of employees per contract type for all the contract types that have more than two employees.
How should you complete the statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

Comprehensive Detailed Explanation
We are tasked with writing a T-SQL query to denormalize the tables Employee and Contract in a Fabric warehouse.
Requirements Breakdown
Include attributes from matching rows in the Contract table
This means we must join Employee and Contract on EmployeeID.
Ensure that all rows from the Employee table are preserved
This requires a LEFT OUTER JOIN from Employee to Contract. If an employee has no contract, we still want the employee record included.
Return the total number of employees per contract type for all contract types that have more than two employees This means we need to:
Group by ContractType
Count distinct EmployeeID
Filter groups where that count > 2.
To filter aggregated results, we use HAVING, not WHERE.
Completed Query
WITH result AS (
SELECT
e.EmployeeID,
e.EmployeeName,
e.EmployeePosition,
c.ContractType,
c.StartDate
FROM Employee AS e
LEFT OUTER JOIN Contract AS c
ON c.EmployeeID = e.EmployeeID
)
SELECT
ContractType,
COUNT(DISTINCT EmployeeID) AS TotalEmployees
FROM result
GROUP BY ContractType
HAVING COUNT(DISTINCT EmployeeID) > 2;
Why This is Correct
LEFT OUTER JOIN ensures all employees are included, regardless of contracts.
HAVING allows filtering aggregated groups by employee counts.
The query returns ContractType, StartDate (as requested in denormalization), and aggregated employee counts.
References
T-SQL JOINs in Microsoft Fabric
Aggregate functions and HAVING clause
Denormalization best practices in Fabric warehouses


NEW QUESTION # 38
You have an Azure SQL database named DB1 and a Fabric workspace named Workspace1. Workspace 1 contains a lakehouse named LH1 and a Dataflow Gen2 named Dataflow1. Dataflow1 includes a query named Query1 that loads data from DB1. applies transformations to the data, and then filters the data.
You discover that Query1 loads all the data before applying the transformations.
You need to ensure that Query1 uses query folding.
What should you do?

Answer: D


NEW QUESTION # 39
Hotspot Question
You have a Fabric tenant that contains a warehouse named Warehouse1. Warehouse1 contains three schemas named schemaA, schemaB, and schemaC.
You need to ensure that a user named User1 can truncate tables in schemaA only.
How should you complete the T-SQL statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 40
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.

Answer: D,E


NEW QUESTION # 41
You have a Fabric tenant that contains a lakehouse named lakehouse1. Lakehouse1 contains an unpartitioned table named Table1.
You plan to copy data to Table1 and partition the table based on a date column in the source data.
You create a Copy activity to copy the data to Table1.
You need to specify the partition column in the Destination settings of the Copy activity.
What should you do first?

Answer: D

Explanation:
Before specifying the partition column in the Destination settings of the Copy activity, you should set Mode to Append (A). This will allow the Copy activity to add data to the table while taking the partition column into account. References = The configuration options for Copy activities and partitioning in Azure Data Factory, which are applicable to Fabric dataflows, are outlined in the official Azure Data Factory documentation.


NEW QUESTION # 42
......

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