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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 (Q60-Q65):

NEW QUESTION # 60
You have a Microsoft Power Bl semantic model that contains a table named Date. Date contains the following data.

You need to ensure that the visuals that use the Date table appear in chronological order. The solution must minimize administrative effort.
What should you do?

Answer: C


NEW QUESTION # 61
You have a Fabric tenant that contains two workspaces named Workspace1 and Workspace2 and a user named User1.
You need to ensure that User1 can perform the following tasks:
* Create a new domain.
* Create two subdomains named subdomain1 and subdomain2.
* Assign Workspace1 to subdomain1.
* Assign Workspace2 to subdomain2.
The solution must follow the principle of least privilege.
Which role should you assign to User1?

Answer: B


NEW QUESTION # 62
You have a Fabric tenant.
You plan to create a Fabric notebook that will use Spark DataFrames to generate Microsoft Power Bl visuals.
You run the following code.

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:
The code embeds an existing Power BI report. - No
The code creates a Power BI report. - Yes
The code displays a summary of the DataFrame. - Yes
The code provided seems to be a snippet from a SQL query or script which is neither creating nor embedding a Power BI report directly. It appears to be setting up a DataFrame for use within a larger context, potentially for visualization in Power BI, but the code itself does not perform the creation or embedding of a report.
Instead, it ' s likely part of a data processing step that summarizes data.
References =
Introduction to DataFrames - Spark SQL
Power BI and Azure Databricks


NEW QUESTION # 63
You have the following T-SQL statement.

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:


NEW QUESTION # 64
You have a Fabric tenant that contains a Microsoft Power Bl report named Report 1.
Report1 is slow to render. You suspect that an inefficient DAX query is being executed.
You need to identify the slowest DAX query, and then review how long the query spends in the formula engine as compared to the storage engine.
Which five actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:


NEW QUESTION # 65
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