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Microsoft DP-600 Exam Syllabus Topics:

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

>> DP-600 Ausbildungsressourcen <<

DP-600 Originale Fragen, DP-600 Zertifizierungsantworten

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Microsoft Implementing Analytics Solutions Using Microsoft Fabric DP-600 Prüfungsfragen mit Lösungen (Q132-Q137):

132. Frage
You are implementing two dimension tables named Customers and Products in a Fabric warehouse.
You need to use slowly changing dimension (SCO) to manage the versioning of data. The solution must meet the requirements shown in the following table.

Which type of SCD should you use for each table? To answer, drag the appropriate SCD types to the correct tables. Each SCD type may be used once, more than once, or not at all. You may need to drag the split bar between panes o r scroll to view content.
NOTE: Each correct selection is worth one point.

Antwort:

Begründung:

Explanation:

For the Customers table, where the requirement is to create a new version of the row, you would use:
Type 2 SCD: This type allows for the creation of a new record each time a change occurs, preserving the history of changes over time.
For the Products table, where the requirement is to overwrite the existing value in the latest row, you would use:
Type 1 SCD: This type updates the record directly, without preserving historical data.


133. Frage
Hotspot Question
You have a Fabric warehouse that contains the following data.

The data has the following characteristics:
- Each customer is assigned a unique CustomerID value.
- Each customer is associated to a single SalesRegion value.
- Each customer is associated to a single CustomerAddress value.
- The Customer table contains 5 million rows.
- All foreign key values are non-null.
You need to create a view to denormalize the data into a customer dimension that contains one row per distinct CustomerID value. The solution must minimize query processing time and resources.
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.

Antwort:

Begründung:


134. Frage
You have a semantic model that contains the following tables:
* Sales
* Product
* Location
You are creating a DAX measure named Measure1 that will calculate the percentage of all the sales of a selected product. Heasure1 will use the following DAX formula.

For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

Antwort:

Begründung:

Explanation:


135. Frage
You have a Fabric tenant that contains a workspace named Workspace1. Workspace1 contains a lakehouse named I.H1 and a warehouse named DW1. I.H1 contains a table named signindata that is in the dho schema.
You need to create a stored procedure in DW1 that deduplicates the data in the signindata table.
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.

Antwort:

Begründung:

Explanation:

Scenario Recap
Fabric tenant # Workspace1
Contains:
Lakehouse LH1 (with table signindata in schema dho)
Warehouse DW1
Task: Create a stored procedure in DW1 that deduplicates rows in signindata.
Step 1: Stored procedure structure
In T-SQL, stored procedures begin with:
AS
BEGIN
-- logic
END
So the correct option for the first blank is BEGIN.
BEGIN DISTRIBUTED TRANSACTION is not needed because we are not spanning multiple servers or needing distributed transactions.
SET is not the right way to start the logic block.
Step 2: Deduplication logic
To remove duplicates from signindata, the query should return unique rows.
The simplest way is:
SELECT DISTINCT PersonID, FirstName, LastName
FROM dho.signindata;
Thus the correct choice for the second blank is DISTINCT.
GROUP BY could also deduplicate but is less efficient here since no aggregation is requested.
TOP 100 PERCENT WITH TIES is irrelevant.
Step 3: Final T-SQL stored procedure
CREATE PROCEDURE dbo.usp_GetPerson
AS
BEGIN
SELECT DISTINCT PersonID, FirstName, LastName
FROM dho.signindata;
END;
Why this is correct
BEGIN # correct stored procedure structure.
DISTINCT # ensures deduplication of rows from signindata.
References
CREATE PROCEDURE (Transact-SQL)
DISTINCT (Transact-SQL)


136. Frage
You need to resolve the issue with the pricing group classification.
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.

Antwort:

Begründung:


137. Frage
......

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