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Microsoft DP-600 Exam Syllabus Topics:

SectionWeightObjectives
Maintain a data analytics solution25–30- Manage analytics development lifecycle
  • 1. Perform impact analysis and dependency management
  • 2. Configure version control and projects
  • 3. Implement deployment pipelines
- Implement security and governance
  • 1. Configure workspace and item-level access
  • 2. Use sensitivity labels and endorsement
  • 3. Apply row-level, column-level, and object-level security
Implement and manage semantic models25–30- Design and build semantic models
  • 1. Define relationships, hierarchies, and measures
  • 2. Optimize model performance and structure
  • 3. Create Power BI semantic models
- Deploy and maintain semantic models
  • 1. Use XMLA endpoint for deployment and management
  • 2. Create reusable assets and shared models
  • 3. Monitor and refresh semantic models
Prepare data for analytics45–50- Implement data storage structures
  • 1. Design and manage lakehouse tables
  • 2. Implement delta lake and partitioning
  • 3. Configure warehouse storage and querying
- Clean and transform data
  • 1. Process data using Spark notebooks and SQL
  • 2. Perform data enrichment and validation
  • 3. Manage data quality and consistency
- Ingest and load data
  • 1. Ingest data from various sources
  • 2. Use Dataflows Gen2 to transform data
  • 3. Load data into lakehouses and warehouses

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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q96-Q101):

NEW QUESTION # 96
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. - No
* 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 # 97
Hotspot Question
You have a Fabric tenant that contains a warehouse named WH1.
You run the following T-SQL query against WH1.

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:


NEW QUESTION # 98
You have a Fabric tenant that contains two workspaces named Workspace1 and Workspace2.
Workspace1 contains a lakehouse named Lakehouse1. Workspace2 contains a lakehouse named Lakehouse2. Lakehouse1 contains a table named dbo.Sales. Lakehouse2 contains a table named dbo.Customers.
You need to ensure that you can write queries that reference both dbo.Sales and dbo.Customers in the same SQL query without making additional copies of the tables.
What should you use?

Answer: A

Explanation:
You can not create view directly. you need to create shortcuts first to access table in different workspaces.


NEW QUESTION # 99
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a Fabric tenant that contains a semantic model named Model1.
You discover that the following query performs slowly against Model1.

You need to reduce the execution time of the query.
Solution: You replace line 4 by using the following code:

Does this meet the goal?

Answer: B

Explanation:
The suggested replacement does not improve performance. COUNTROWS( ' Order Item ' ) < 0 is always false (row counts cannot be negative), so the NOT will always evaluate to true. This means the filter condition becomes non-selective and would return all customers, not just those with orders. Therefore, it does not meet the optimization goal.


NEW QUESTION # 100
You have a Fabric warehouse that contains a table named Sales.Products. Sales.Products contains the following columns.

You need to write a T-SQL query that will return the following columns.

How should you complete the code? To answer, select the appropriate options in the answer area.

Answer:

Explanation:

Explanation:
* For the HighestSellingPrice, you should use the GREATEST function to find the highest value from the given price columns. However, T-SQL does not have a GREATEST function as found in some other SQL dialects, so you would typically use a CASE statement or an IIF statement with nested MAX functions. Since neither of those are provided in the options, you should select MAX as a placeholder to indicate the function that would be used to find the highest value if combining multiple MAX functions or a similar logic was available.
* For the TradePrice, you should use the COALESCE function, which returns the first non-null value in a list. The COALESCE function is the correct choice as it will return AgentPrice if it's not null; if AgentPrice is null, it will check WholesalePrice, and if that is also null, it will return ListPrice.
The complete code with the correct SQL functions would look like this:
SELECT ProductID,
MAX(ListPrice, WholesalePrice, AgentPrice) AS HighestSellingPrice, -- MAX is used as a placeholder COALESCE(AgentPrice, WholesalePrice, ListPrice) AS TradePrice FROM Sales.Products Select MAX for HighestSellingPrice and COALESCE for TradePrice in the answer area.


NEW QUESTION # 101
......

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