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NEW QUESTION: 1
システム管理者が新しいカーネルモジュールを構成しましたが、再起動後に動作しなくなりました。システム管理者がサーバーの起動時にモジュールの問題を確認できるのは、次のうちどれですか？
A. modprobe
B. modinfo
C. dmesg
D. lsmod
Answer: B
Explanation:
Reference:
https://access.redhat.com/documentation/en-us/red_hat_enterprise_linux/6/html/deployment_guide/sec-displaying_information_about_a_module
NEW QUESTION: 2
Which two are requirements when booting from SAN? (Choose Two.)
A. The BIOS for the HBA must be enabled and correctly configured.
B. The boot LUN should only be visible to the ESX Server that is booting from it.
C. The boot LUN should be visible to all ESX Servers for HA failover.
D. Boot LUN must have an ID of 1.
Answer: A,B
NEW QUESTION: 3
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 create a parameter named DataSourceExcel that holds the file name and location of a Microsoft Excel data source.
You need to update the query to reference the parameter instead of multiple hard-coded copies of the location within each query definition.
Solution: You create a new query that references DataSourceExcel.
Does this meet the goal?
A. Yes
B. No
Answer: B
Explanation:
Explanation
Instead modify the source step of the queries to use DataSourceExcel as the file path.
Note: Parameterising a Data Source could be used in many different use cases. From connecting to different data sources defined in Query Parameters to load different combinations of columns.
Reference:
https://www.biinsight.com/power-bi-desktop-query-parameters-part-1/
NEW QUESTION: 4
You are designing a serving layer for data. The design must meet the following requirements:
Authenticate users by using Azure Active Directory (Azure AD).
Serve as a hot path for data.
Support query scale out.
Support SQL queries.
What should you include in the design?
A. Azure Synapse Analytics
B. Azure Blob storage
C. Azure Cosmos DB
D. Azure Data Lake Storage
Answer: C
Explanation:
Explanation
Do you need serving storage that can serve as a hot path for your data? If yes, narrow your options to those that are optimized for a speed serving layer. This would be Cosmos DB among the options given in this question.
Note: Analytical data stores that support querying of both hot-path and cold-path data are collectively referred to as the serving layer, or data serving storage.
There are several options for data serving storage in Azure, depending on your needs:
* Azure Synapse Analytics
* Azure Cosmos DB
* Azure Data Explorer
* Azure SQL Database
* SQL Server in Azure VM
* HBase/Phoenix on HDInsight
* Hive LLAP on HDInsight
* Azure Analysis Services
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/analytical-data-stores