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Microsoft DP-600 Exam Overview:

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

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Microsoft DP-600 Exam Syllabus Topics:

TopicDetails
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 (Q163-Q168):

NEW QUESTION # 163
You have an Amazon Web Services (AWS) subscription that contains an Amazon Simple Storage Service (Amazon S3) bucket named bucketl.
You have a Fabric tenant that contains a lakehouse named LH1.
In LH1, you plan to create a OneLake shortcut to bucketl.
You need to configure authentication for the connection.
Which two values should you provide? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

Answer: B,E

Explanation:
When creating a OneLake shortcut to Amazon S3, authentication uses the standard AWS access key ID + secret access key pair.
SAS token is for Azure Storage, not AWS.
Certificate thumbprint is not used for S3.
Access ID is incorrect naming; the correct term is access key ID.
Correct answers: B and D.
Reference: Create shortcuts to Amazon S3 in OneLake


NEW QUESTION # 164
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 # 165
You have a Fabric workspace that contains a large warehouse.
You plan to create a lakehouse named Lakehousel for a sales dataset. Lakehousel will contain the following tables:
* Sales: Contains sales transactions
* Stores: Contains a unique list of store names and locations
* Loyalty: Contains a list of customers and their preferred stores
* Customers: Contains a unique list of customer names and addresses
* Products: Contains a unique list of available products and their descriptions You need to configure a star schema for Lakehousel.
Which table should you define as the fact table, and which type of relationship should you configure from the Sales table to the Customers table? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 166
You are developing a Microsoft Power BI semantic model. Two tables in the data model are not connected in a physical relationship. You need to establish a virtual relationship between the tables. Which DAX function should you use?

Answer: C


NEW QUESTION # 167
You have a Fabric workspace named Workspace-!. You have a GitHub repository named Repol. You need to connect Workspacel to the main branch of Repol. Which information should you provide?

Answer: D


NEW QUESTION # 168
......

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