[2024年05月]に更新されたMicrosoft Certified DP-600試験練習問題集お試しセット [Q13-Q34]

[2024年05月]に更新されたMicrosoft Certified DP-600試験練習問題集お試しセット

2024年最新のDP-600プレミアム資料テストPDF無料問題集お試しセット

質問 # 13
You have a Fabric tenant that contains a semantic model. The model uses Direct Lake mode.
You suspect that some DAX queries load unnecessary columns into memory.
You need to identify the frequently used columns that are loaded into memory.
What are two ways to achieve the goal? Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.

A. Use the Vertipaq Analyzer tool.
B. Query the discover_hehory6Rant dynamic management view (DMV).
C. Use the Analyze in Excel feature.
D. Query the $system.discovered_STORAGE_TABLE_COLUMN-iN_SEGMeNTS dynamic management view (DMV).

正解：A、D

質問 # 14
You have a Fabric tenant that contains a complex semantic model. The model is based on a star schema and contains many tables, including a fact table named Sales. You need to create a diagram of the model. The diagram must contain only the Sales table and related tables. What should you use from Microsoft Power Bl Desktop?

A. Model view
B. data categories
C. Data view
D. DAX query view

正解：A

質問 # 15
You have a Fabric tenant that contains a warehouse.
You use a dataflow to load a new dataset from OneLake to the warehouse.
You need to add a Power Query step to identify the maximum values for the numeric columns.
Which function should you include in the step?

A. Table.Profile
B. Table.Range
C. Table.Max
D. Table. MaxN

正解：C

質問 # 16
You have a Fabric warehouse that contains a table named Staging.Sales. Staging.Sales contains the following columns.

You need to write a T-SQL query that will return data for the year 2023 that displays ProductID and ProductName arxl has a summarized Amount that is higher than 10,000. Which query should you use?

正解：B

質問 # 17
You have a Fabric workspace that contains a DirectQuery semantic model. The model queries a data source that has 500 million rows.
You have a Microsoft Power Bl report named Report1 that uses the model. Report! contains visuals on multiple pages.
You need to reduce the query execution time for the visuals on all the pages.
What are two features that you can use? Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.

A. automatic aggregation
B. OneLake integration
C. user-defined aggregations
D. query caching

正解：A、C

質問 # 18
You need to create a data loading pattern for a Type 1 slowly changing dimension (SCD).
Which two actions should you include in the process? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.

A. Update rows when the non-key attributes have changed.
B. Update the effective end date of rows when the non-key attribute values have changed.
C. Insert new records when the natural key is a new value in the table.
D. Insert new rows when the natural key exists in the dimension table, and the non-key attribute values have changed.

正解：A、C

質問 # 19
You have a Fabric tenant that contains a warehouse named Warehouse1. Warehouse1 contains a fact table named FactSales that has one billion rows. You run the following T-SQL statement.
CREATE TABLE test.FactSales AS CLONE OF Dbo.FactSales;
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

正解：

解説：

質問 # 20
You have a Fabric tenant that contains a new semantic model in OneLake.
You use a Fabric notebook to read the data into a Spark DataFrame.
You need to evaluate the data to calculate the min, max, mean, and standard deviation values for all the string and numeric columns.
Solution: You use the following PySpark expression:
df.show()
Does this meet the goal?

A. Yes
B. No

正解：B

質問 # 21
You have a Fabric tenant that contains a warehouse. The warehouse uses row-level security (RLS). You create a Direct Lake semantic model that uses the Delta tables and RLS of the warehouse. When users interact with a report built from the model, which mode will be used by the DAX queries?

A. Direct Lake
B. DirectQuery
C. Dual
D. Import

正解：A

質問 # 22
You have a Fabric tenant tha1 contains a takehouse 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:
REFRESH TABLE customer
Does this meet the goal?

A. Yes
B. No

正解：B

質問 # 23
You have a Fabric tenant tha1 contains a takehouse 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:
EXPLAIN TABLE customer
Does this meet the goal?

A. Yes
B. No

正解：B

質問 # 24
You have a Fabric tenant that contains a lakehouse named Lakehouse1
Readings from 100 loT devices are appended to a Delta table in Lakehouse1. Each set of readings is approximately 25 KB. Approximately 10 GB of data is received daily.
All the table and SparkSession settings are set to the default.
You discover that queries are slow to execute. In addition, the lakehouse storage contains data and log files that are no longer used.
You need to remove the files that are no longer used and combine small files into larger files with a target size of 1 GB per file.
What should you do? To answer, drag the appropriate actions to the correct requirements. Each action 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.

正解：

解説：

質問 # 25
Which type of data store should you recommend in the AnalyticsPOC workspace?

A. an external Hive metaStore
B. a warehouse
C. a data lake
D. a lakehouse

正解：D

質問 # 26
You have a Fabric tenant that contains a lakehouse.
You are using a Fabric notebook to save a large DataFrame by using the following code.

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

正解：

解説：

質問 # 27
You have the source data model shown in the following exhibit.

The primary keys of the tables are indicated by a key symbol beside the columns involved in each key.
You need to create a dimensional data model that will enable the analysis of order items by date, product, and customer.
What should you include in the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解：

解説：

質問 # 28
You have a Fabric tenant that contains a workspace named Workspace^ Workspacel is assigned to a Fabric capacity.
You need to recommend a solution to provide users with the ability to create and publish custom Direct Lake semantic models by using external tools. The solution must follow the principle of least privilege.
Which three actions in the Fabric Admin portal should you include in the recommendation? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.

A. From the Tenant settings, set Users can create Fabric items to Enabled
B. From the Tenant settings, set Allow Azure Active Directory guest users to access Microsoft Fabric to Enabled
C. From the Tenant settings, set Allow XMLA Endpoints and Analyze in Excel with on-premises datasets to Enabled
D. From the Tenant settings, enable Publish to Web
E. From the Capacity settings, set XMLA Endpoint to Read Write
F. From the Tenant settings, select Users can edit data models in the Power Bl service.

正解：C、D、E

質問 # 29
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?

A. ReadTable2.
B. ReadTable3.
C. Update the data in Table1.
D. Update the data Table3.

正解：C

質問 # 30
You have a Microsoft Power B1 report and a semantic model that uses Direct Lake mode. From Power Si Desktop, you open Performance analyzer as shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic. NOTE: Each correct selection is worth one point.

正解：

解説：

質問 # 31
You have a Fabric tenant that contains a lakehouse named lakehouse1. Lakehouse1 contains an unpartitioned table named Table1.
You plan to copy data to Table1 and partition the table based on a date column in the source data.
You create a Copy activity to copy the data to Table1.
You need to specify the partition column in the Destination settings of the Copy activity.
What should you do first?

A. From the Destination tab, set Mode to Append.
B. From the Source tab, select Enable partition discovery
C. From the Destination tab, select the partition column,
D. From the Destination tab, set Mode to Overwrite.

正解：C

質問 # 32
You have a Fabric tenant that contains a Microsoft Power Bl report named Report 1. Report1 includes a Python visual. Data displayed by the visual is grouped automatically and duplicate rows are NOT displayed. You need all rows to appear in the visual. What should you do?

A. Reference the columns in the Python code by index.
B. Add a unique field to each row.
C. Modify the Sort Column By property for all columns.
D. Modify the Summarize By property for all columns.

正解：B

質問 # 33
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.