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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement and manage semantic models | 25–30 | - Design and build semantic models
|
| Topic 2: Prepare data for analytics | 45–50 | - Ingest and load data
|
| Topic 3: Maintain a data analytics solution | 25–30 | - Implement security and governance
|
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NEW QUESTION # 37
You have a Fabric workspace named Workspace1 that is assigned to a newly created Fabric capacity named Capacity1.
You create a semantic model named Model1 and deploy Model1 to Workspace1.
You need to publish changes to Model1 directly from Tabular Editor.
What should you do?
Answer: A
NEW QUESTION # 38
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 lakehouse named Lakehouse1. Lakehouse1 contains a Delta table named Customer.
When you query Customer, you discover that the query is slow to execute. You suspect that maintenance was NOT performed on the table.
You need to identify whether maintenance tasks were performed on Customer.
Solution: You run the following Spark SQL statement:
DESCRIBE DETAIL customer
Does this meet the goal?
Answer: A
Explanation:
Describe Detail give general info about delta table, not the historical operations.
https://learn.microsoft.com/en-us/azure/databricks/delta/table-details
NEW QUESTION # 39
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:
NEW QUESTION # 40
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:
Explanation:
Step 1 - Select the required fields and count
We want to group by CustomerAltKey and count occurrences.
SELECT CustomerAltKey, COUNT ( * )
Step 2 - From the table
FROM DimCustomer
Step 3 - Grouping by email
GROUP BY CustomerAltKey
Step 4 - Filtering duplicates (only values with count > 1)
HAVING COUNT ( * ) > 1
Step 5 - Limiting the result to 1,000 rows
LIMIT 1000
(or in T-SQL, SELECT TOP(1000) ... ). Since both options are shown, we use LIMIT 1000 because Fabric Warehouse supports Synapse SQL T-SQL + ANSI SQL style.
Correct Sequence:
SELECT CustomerAltKey, COUNT(*)
FROM DimCustomer
GROUP BY CustomerAltKey
HAVING COUNT(*) > 1
LIMIT 1000
NEW QUESTION # 41
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.
Answer:
Explanation:
Explanation:
You should use CREATE VIEW to make the pricing group logic available for T-SQL queries.
The CASE statement should be used to determine the pricing group based on the list price.
The T-SQL statement should create a view that classifies products into pricing groups based on the list price.
The CASE statement is the correct conditional logic to assign each product to the appropriate pricing group.
This view will standardize the pricing group logic across different databases and semantic models.
NEW QUESTION # 42
......
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