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Microsoft DP-600 Exam Syllabus Topics:

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

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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q112-Q117):

NEW QUESTION # 112
You have a Fabric tenant that contains a workspace named Workspace1. Workspace1 contains a lakehouse named Lakehouse1 and a warehouse named Warehouse1.
You need to create a new table in Warehouse1 named POSCustomers by querying the customer table in Lakehouse1.
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.

Answer:

Explanation:

Explanation:

Step 1 - Creating the new table from a query
To create a table in a SQL warehouse using a query, the correct syntax is:
CREATE TABLE < table_name > AS SELECT ...
So we must select:
CREATE TABLE dbo.POSCustomers AS SELECT
Step 2 - Selecting the source table
Since the data source is the Lakehouse1 table Customer, the fully qualified name is:
lakehouse1.dbo.Customer
Final Answer:
CREATE TABLE dbo.POSCustomers AS SELECT
postalcode,
category
FROM lakehouse1.dbo.Customer;
References:
CREATE TABLE AS SELECT (CTAS) in Fabric Warehouse
Fabric Lakehouse and Warehouse interoperability


NEW QUESTION # 113
You have a data warehouse that contains a table named Stage. Customers. Stage-Customers contains all the customer record updates from a customer relationship management (CRM) system. There can be multiple updates per customer You need to write a T-SQL query that will return the customer ID, name, postal code, and the last updated time of the most recent row for each customer ID.
How should you complete the code? To answer, select the appropriate options in the answer area, NOTE Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

* In the ROW_NUMBER() function, choose OVER (PARTITION BY CustomerID ORDER BY LastUpdated DESC).
* In the WHERE clause, choose WHERE X = 1.
To select the most recent row for each customer ID, you use the ROW_NUMBER() window function partitioned by CustomerID and ordered by LastUpdated in descending order. This will assign a row number of 1 to the most recent update for each customer. By selecting rows where the row number (X) is 1, you get the latest update per customer.
References =
* Use the OVER clause to aggregate data per partition
* Use window functions


NEW QUESTION # 114
You have the following T-SQI statement.

Answer:

Explanation:

Explanation:

The statement uses SUM(CASE WHEN RefundStatus = ' Refunded ' THEN SalesAmount ELSE 0 END) AS TotalRevenue, which calculates TotalRevenue by summing SalesAmount only when RefundStatus is ' Refunded ' , and 0 otherwise. This means Region values are returned regardless of RefundStatus, but the TotalRevenue reflects refunded items.
The WHERE (TransactionDate) - YEAR(GETDATE()) condition is incomplete and lacks proper comparison (e.g., no equality or range check), so it does not filter for the current year.
The TotalRevenue calculation does not aggregate all SalesAmount values with RefundStatus of ' Refunded ' ; it sums SalesAmount only for refunded items within the grouped data, with 0 for non-refunded items.


NEW QUESTION # 115
You have a Fabric tenant that contains a warehouse named Warehouse1. Warehouse1 contains three schemas named schemaA, schemaB. and schemaC You need to ensure that a user named User1 can truncate tables in schemaA only.
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.

Answer:

Explanation:

Explanation:

* GRANT ALTER ON SCHEMA::schemaA TO User1;
The ALTER permission allows a user to modify the schema of an object, and granting ALTER on a schema will allow the user to perform operations like TRUNCATE TABLE on any object within that schema. It is the correct permission to grant to User1 for truncating tables in schemaA.
References =
* GRANT Schema Permissions
* Permissions That Can Be Granted on a Schema


NEW QUESTION # 116
You have a Fabric warehouse that contains a table named SalesOrderDetail. SalesOrderDetail contains three columns named OrderQty, ProductID and SalesOrderlD. SalesOrderDetail contains one row per combination of SalesOrderlD and ProductID.
You need to calculate the proportion of the total quantity of each sales order represented by each product within the sales order.
Which T-SQL statement should you run?

Answer: B

Explanation:
Comprehensive Detailed Explanation
We need to calculate the proportion of the total quantity of each sales order represented by each product within the sales order .
Step 1: Analyze the requirement
Table: SalesOrderDetail
Columns: OrderQty , ProductID , SalesOrderID
Each row = one product in a sales order.
Requirement: For each SalesOrderID , calculate what percentage each product contributes to the total order quantity.
This means we must:
Calculate the total order quantity per SalesOrderID .
Divide each product's OrderQty by that total.
Express it as a percentage.
Step 2: Evaluate the options
A). Uses OVER(ORDER BY ProductID)
Wrong: ORDER BY does not segment data, it only defines sequence. We need grouping by sales order.
B). Uses OVER(PARTITION BY ProductID)
Wrong: This would calculate percentages per product across all sales orders, not per sales order.
C). Uses OVER(PARTITION BY SalesOrderID)
Correct: This computes the total OrderQty per SalesOrderID and divides each product's quantity by that total.
Exactly what the requirement asks.
D). Uses OVER(ORDER BY SalesOrderID)
Wrong: Again, ORDER BY just sequences rows, does not group them.
Step 3: Correct Query
SELECT
SalesOrderID,
ProductID,
OrderQty,
CAST ( 1. * OrderQty / SUM (OrderQty)
OVER ( PARTITION BY SalesOrderID) * 100 AS DECIMAL ( 5 , 2 ))
AS PercentByProductID
FROM Sales.SalesOrderDetail;
Why Option C is Correct
PARTITION BY SalesOrderID ensures the denominator is the total quantity for the current order .
This produces the correct percentage breakdown of each product inside its sales order.
References
T-SQL Window Functions
Aggregate Functions with PARTITION BY
Microsoft Fabric Warehouse T-SQL Support


NEW QUESTION # 117
......

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