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Microsoft DP-600 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Load and prepare data20-25%- Ingest data from source systems
  • 1. Configure Data Gateway for hybrid scenarios
  • 2. Ingest data using PySpark or Spark SQL
  • 3. Use Data Factory data flow for transformation
  • 4. Implement streaming data ingestion with Eventstream
  • 5. Use Data Factory copy activity for batch ingestion
- Create and configure items
  • 1. Configure data processing with notebooks
  • 2. Create and configure Lakehouse, Warehouse, or data pipeline
  • 3. Create and configurehortcuts
Topic 2: Secure and monitor data solutions15-20%- Monitor data solutions
  • 1. Monitor pipeline and dataflow execution
  • 2. Use OneLake monitoring capabilities
  • 3. Implement alerting and notifications
  • 4. Review and analyze capacity metrics
- Secure data solutions
  • 1. Configure sensitive data classifications
  • 2. Use Microsoft Purview for data governance
  • 3. Implement column-level and row-level security
  • 4. Configure workspace and item permissions
Topic 3: Deploy and maintain a data solution10-15%- Deploy data assets
  • 1. Use deployment pipelines for development to production
  • 2. Implement CI/CD for Fabric items
  • 3. Automate deployments using APIs and scripts
- Maintain a data solution
  • 1. Manage workspace and capacity settings
  • 2. Implement data refresh strategies
  • 3. Optimize query performance
Topic 4: Design and manage the data model20-25%- Implement and configure a data model
  • 1. Use DirectLake mode for large datasets
  • 2. Implement row-level security (RLS)
  • 3. Configure SQL analytics endpoint
  • 4. Create and manage semantic models
- Design a data model
  • 1. Define relationships and hierarchies
  • 2. Choose appropriate data model type (lakehouse vs warehouse)
  • 3. Implement dimension and fact tables
  • 4. Design a star or snowflake schema
Topic 5: Clean, transform, and enrich data25-30%- Transform data
  • 1. Use Dataflow Gen2 for transformations
  • 2. Perform schema evolution and mapping
  • 3. Use Spark libraries for data transformation
  • 4. Implement data standardization and normalization
- Enrich data
  • 1. Implement slowly changing dimensions (SCD)
  • 2. Merge and join data sources
  • 3. Implement incremental data loading
- Clean data
  • 1. Handle missing values and duplicates
  • 2. Validate data quality using Data Quality Profiling
  • 3. Apply data cleansing techniques

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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q37-Q42):

NEW QUESTION # 37
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:

Explanation:

We are analyzing the query:
SELECT e.[WWI Employee ID],
e.Employee,
e.[Preferred Name],
gdr.[WWI Employee ID] AS [Direct Report ID],
gdr.Employee AS [Direct Report]
FROM Dimension.Employee AS e
OUTER APPLY Dimension.GetDirectReports(e.[Employee Key]) AS gdr;
Key concepts:
APPLY operator: Used to join a table with a table-valued function.
OUTER APPLY ensures all rows from the left (Employee) are returned, even if the function returns no rows (similar to LEFT JOIN).
Table-valued function (TVF): Returns a set of rows (unlike scalar functions, which return a single value).
The function executes once per row from the left table, not once for the whole query.
Evaluating each statement:
"Dimension.GetDirectReports is a scalar T-SQL function."
No # It must be a table-valued function, because OUTER APPLY requires a table expression.
"The Dimension.GetDirectReports function will run only once when the query runs." No # With APPLY, the function runs for each row of Dimension.Employee.
"The output rows will include at least one row for each row in the Dimension.Employee table." Yes # Because of OUTER APPLY, every employee row is included, even if there are no direct reports (in that case, the columns from gdr will be NULL).
Final Answer:
Scalar function # No
Runs once per query # No
At least one row per Employee # Yes
References:
APPLY operator in T-SQL
Table-valued functions


NEW QUESTION # 38
You have a Fabric tenant that contains a data warehouse named DW1. DW1 contains a table named DimCustomer. DimCustomer contains the fields shown in the following table.

You need to identify duplicate email addresses in DimCustomer. The solution must return a maximum of 1,000 records.
Which four T-SQL statements should you run in sequence? To answer, move the appropriate statements from the list of statements to the answer area and arrange them in the correct order.

Answer:

Explanation:


NEW QUESTION # 39
You have a Fabric tenant named Tenant1 that contains a workspace named WS1. WS1 uses a capacity named C1 and contains a dataset named DS1.
You need to ensure read-write access to DS1 is available by using XMLA endpoint.
What should be modified first?

Answer: C

Explanation:
https://learn.microsoft.com/en-us/power-bi/enterprise/service-premium-connect-tools


NEW QUESTION # 40
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:

Explanation:

We are analyzing the query:
SELECT e.[WWI Employee ID],
e.Employee,
e.[Preferred Name],
gdr.[WWI Employee ID] AS [Direct Report ID] ,
gdr.Employee AS [Direct Report]
FROM Dimension.Employee AS e
OUTER APPLY Dimension.GetDirectReports(e.[Employee Key]) AS gdr;
Key concepts:
APPLY operator: Used to join a table with a table-valued function.
OUTER APPLY ensures all rows from the left (Employee) are returned, even if the function returns no rows (similar to LEFT JOIN).
Table-valued function (TVF): Returns a set of rows (unlike scalar functions, which return a single value).
The function executes once per row from the left table, not once for the whole query.
Evaluating each statement:
" Dimension.GetDirectReports is a scalar T-SQL function. "
No # It must be a table-valued function, because OUTER APPLY requires a table expression.
" The Dimension.GetDirectReports function will run only once when the query runs. " No # With APPLY, the function runs for each row of Dimension.Employee.
" The output rows will include at least one row for each row in the Dimension.Employee table. " Yes # Because of OUTER APPLY, every employee row is included, even if there are no direct reports (in that case, the columns from gdr will be NULL).
Final Answer:
Scalar function # No
Runs once per query # No
At least one row per Employee # Yes
References:
APPLY operator in T-SQL
Table-valued functions


NEW QUESTION # 41
You have a Microsoft Power BI solution.
You need to recommend a development format that meets the following requirements:
Supports Git integration
Supports object-level diff review in source controls
Enables semantic models and report definitions to be stored as readable text files What should you recommend?

Answer: C


NEW QUESTION # 42
......

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