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질문 # 32
You are the administrator of a Fabric workspace that contains a lakehouse named Lakehouse1. Lakehouse1 contains the following tables:
* Table1: A Delta table created by using a shortcut
* Table2: An external table created by using Spark
* Table3: A managed table
You plan to connect to Lakehouse1 by using its SQL endpoint. What will you be able to do after connecting to Lakehouse1?
정답：D
질문 # 33
You have a Fabric workspace that contains a warehouse named DW1. DW1 contains the following tables and columns.
You need to summarize order quantities by year and product. The solution must include the yearly sum of order quantities for all the products in each row.
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.
정답：
설명：
Explanation:
Comprehensive Detailed Explanation
We need to write a query that summarizes order quantities by year and product , and also include the yearly total for all products in each row.
Step 1: What the query needs
Extract the year from SalesOrderDetail.ModifiedDate .
Join with the Product table to get the product name.
Aggregate with SUM(OrderQty) .
Return grouped data by year and product , with an additional subtotal row per year (all products combined).
Step 2: Evaluate the SELECT Clause
We must extract the year using:
YEAR (so.ModifiedDate) AS OrderDate
This converts the ModifiedDate column into a year value for grouping.
Step 3: Evaluate the GROUP BY options
CUBE(YEAR, P.Name) # Produces all combinations of year totals, product totals, and grand totals. Too many combinations, not required.
GROUPING SETS # Could achieve the result but requires explicitly listing the sets. Less direct.
ROLLUP(YEAR, P.Name) # Produces grouping by (Year, Product) and then a subtotal per Year. Exactly what is required.
YEAR only # Would group only by year, losing per-product breakdown.
Correct: ROLLUP(YEAR(so.ModifiedDate), P.Name)
Step 4: Completed Query
SELECT
YEAR (so.ModifiedDate) AS OrderDate,
p.Name,
SUM (so.OrderQty) AS OrderQty
FROM dbo.SalesOrderDetail so
INNER JOIN dbo.Product p
ON p.ProductID = so.ProductID
GROUP BY ROLLUP ( YEAR (so.ModifiedDate), p.Name);
Why This Works
YEAR(so.ModifiedDate) extracts year for grouping.
ROLLUP(YEAR, P.Name) provides both product-level totals and yearly subtotals.
Ensures the requirement: "include the yearly sum of order quantities for all the products in each row." References GROUP BY ROLLUP in T-SQL Aggregate functions in Microsoft Fabric warehouses
질문 # 34
You have two Microsoft Power Bl queries named Employee and Retired Roles.
You need to merge the Employee query with the Retired Roles query. The solution must ensure that rows in the Employee query that match the Retired Roles query are removed.
Which column and Join Kind should you use in Power Query Editor? To answer, select the appropriate options in the answer area.
NOTE: Each correct answer is worth one point
정답：
설명：
Explanation:
질문 # 35
You have a Fabric tenant that contains the workspaces shown in the following table.
You have a deployment pipeline named Pipeline1 that deploys items from Workspace_DEV to Workspace_TEST. In Pipeline1, all items that have matching names are paired.
You deploy the contents of Workspace_DEV to Workspace_TEST by using Pipeline1.
What will the contents of Workspace_TEST be once the deployment is complete?
정답：D
설명：
Work space_DEV contents:
Lakehouse1, Notebook1, Pipeline1, SemanticModel1
Workspace_TEST contents (before deployment):
Lakehouse2, Notebook2, SemanticModel1
After deployment:
SemanticModel1 # same name, so it will be paired and overwritten with the DEV version.
Lakehouse1 and Notebook1 # new items, so they will be added to TEST.
Lakehouse2 and Notebook2 # remain because they don't conflict in name.
Pipeline1 # new item, so it will also be added .
So the final content is:
Lakehouse1, Lakehouse2, Notebook1, Noteboo k2, Pipeline1, SemanticModel1 Reference:
Deployment pipelines pairing behavior
질문 # 36
Drag and Drop Question
You have a Fabric lakehouse named Lakehouse1.
You have the data sources shown in the following table.
You need to ingest data from both data sources into Lakehouse1. The solution must minimize maintenance and development time.
What should you use to ingest the data into each data source? To answer, drag the appropriate options to the correct data sources. 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.
정답：
설명：
Explanation:
Box 1: ADLS Gen2
Contains data from an Azure SQL managed instance that has a change data capture (CDC) enabled for all tables.
Has a daily data load that is more than 500,000 rows and 20 GB.
Change data capture in Azure Data Factory and Azure Synapse Analytics.
Auto incremental extraction in mapping data flow.
The newly updated rows or updated files can be automatically detected and extracted by ADF mapping data flow from the source stores. When you want to get delta data from the databases, the incremental column is required to identify the changes. When you want to load new files or updated files only from a storage store, ADF mapping data flow just works through files' last modify time.
Box 2: An eventstream
Contains data from a manufacturing machine that includes the item count, item weight, and item volume.
Contains data that is streamed to an Azure event hub in Azure.
Reference:
https://learn.microsoft.com/en-us/azure/data-factory/concepts-change-data-capture
https://learn.microsoft.com/en-us/fabric/real-time-intelligence/event-streams/transform-and- stream-real-time-events-to-lakehouse
질문 # 37
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