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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Implementing Analytics Solutions Using Microsoft Fabric |
| Exam Number: | DP-600 |
| Certificate Validity Period: | 1 year |
| Real Exam Qty: | 40-60 |
| Available Languages: | Korean, Chinese (Simplified), English, Japanese |
| Passing Score: | 700/1000 |
| Related Certifications: | Microsoft Certified: Fabric Analytics Engineer Associate |
| Exam Duration: | 120 minutes |
| Exam Format: | Multiple-choice, Case studies, Drag-and-drop |
| Exam Price: | $165 USD |
| Sample Questions: | Microsoft DP-600 Sample Questions |
| Exam Way: | Online proctored or in-person testing center |
| Pre Condition: | Candidates should have foundational knowledge of data concepts, experience with Microsoft Fabric, and proficiency in data transformation and modeling. Familiarity with Power BI is recommended but not required. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/certifications/exams/dp-600 |
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NEW QUESTION # 156
You are implementing a medallion architecture in a single Fabric workspace.
You have a lakehouse that contains the 8ronze and Silver layers and a warehouse that contains the Gold layer.
You create the items required to populate the layers as shown in the following table.
You need to ensure that the layers are populated daily in sequential order such that Silver is populated only after Bronze is complete, and Gold is populated only after Silver is complete. The solution must minimize development effort and complexity.
What should you use to execute each set of items? To answer, drag the appropriate options to the correct items. Each option may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
To execute each set of items in sequential order with minimized development effort and complexity, you should use the following options:
* Orchestration pipeline: Use a pipeline with an Invoke pipeline activity. This allows for orchestrating and scheduling the execution of other pipelines, ensuring they run in the correct sequence.
* Bronze layer: Implement a pipeline Copy activity. This aligns with the table indicating that the Bronze layer uses pipelines with Copy activities for data integration.
* Silver layer: Implement a pipeline Dataflow activity. The table specifies that Dataflows are used for the Silver layer.
* Gold layer: Implement a pipeline Stored procedure activity. Stored procedures are specified for the Gold layer according to the table.
NEW QUESTION # 157
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 # 158
You have a Fabric workspace named Workspace1.
Workspace1 contains multiple semantic models, including a model named Model1. Model1 is updated by using an XMLA endpoint.
You need to increase the speed of the write operations of the XMLA endpoint.
What should you do?
Answer: B
Explanation:
When using XMLA endpoints to manage and update semantic models in Microsoft Fabric, the performance of write operations (such as processing, structural changes, or metadata deployments from Tabular Editor) is directly influenced by the storage format and how the model is persisted.
Why Option A is Correct
* By default, Fabric semantic models use the Small semantic model storage format.
* To improve write operations performance through XMLA, you must change the workspace setting to use the Large semantic model storage format.
* The large format uses more efficient storage techniques, supports partitioning, and handles larger models with optimized write capabilities.
* This setting is applied at the workspace level and impacts all semantic models within that workspace, including Model1.
This is explicitly documented in Microsoft's guidance: Large semantic model storage format is required when using XMLA write operations for large or frequently updated models.
Why the Other Options Are Incorrect
B). Configure Model1 to use the Direct Lake storage format.
* Direct Lake mode is designed for query performance (reading data directly from OneLake in delta format without import/duplication).
* It improves query latency and freshness but does not improve XMLA write operations, which deal with model metadata and structural updates.
C). Delete any unused semantic models from Workspace1.
* Deleting unused semantic models helps manage capacity and storage but does not increase the speed of XMLA endpoint write operations.
* Workspace storage overhead does not directly impact the write throughput of XMLA operations.
D). Delete any unused columns from Model1.
* Removing unused columns reduces the memory footprint and can improve query performance.
* However, it does not directly improve the speed of XMLA write operations. The bottleneck in XMLA writes is tied to the storage format, not the model size alone.
Summary
To increase the speed of XMLA write operations on semantic models, you must enable the Large semantic model storage format at the workspace level. This setting ensures better handling of writes and metadata operations via the XMLA endpoint.
References
* Large models in Power BI and Microsoft Fabric
* Use the XMLA endpoint in Microsoft Fabric
* Manage capacities in Microsoft Fabric
NEW QUESTION # 159
You have a Fabric workspace named Workspacel that uses the Premium Per User (PPU) license mode and contains a semantic model named Model1.
Large semantic model storage format is selected for Model 1.
You need to ensure that tables imported into Modell are written automatically to Delta tables in OneLake.
What should you do for Modell and Workspacel? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 160
You have the following KQL query.
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 this KQL query:
Sales
| where Status != " Cancelled "
| where OrderDate > = ago(30d)
| summarize TotalSales = sum(SalesAmount) by ProductCategory
| where TotalSales > 0
Statement 1:
" The query excludes sales that have a Status of Cancelled. "
Yes # where Status != " Cancelled " filters them out.
Statement 2:
" The query calculates the total sales of each product category for the last 30 days. " Yes # where OrderDate > = ago(30d) ensures only last 30 days.
summarize TotalSales = sum(SalesAmount) by ProductCategory groups by category.
Statement 3:
" The query includes product categories that have had zero sales during the last 30 days. " No # The final filter where TotalSales > 0 excludes categories with zero sales.
Excludes Cancelled sales # Yes
Calculates total sales by product category for last 30 days # Yes
Includes product categories with zero sales # No
References:
KQL where operator
KQL summarize operator
NEW QUESTION # 161
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