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NEW QUESTION: 1
A tape library had the robot firmware upgraded and now the robot is reading the barcodes with additional characters.
How should an administrator enable NetBackup 8.0to use the same characters as before the firmware upgrade occurred?
A. update Device mappings
B. update the Barcode Rules setting
C. update Media settings
D. update the Media ID Generation setting
Answer: D
NEW QUESTION: 2
Answer:
Explanation:
Explanation:
Scenario:
You must implement auditing for all objects in the ADVSchema schema.
Box 1: CREATE SERVER AUDIT
Create the server audit.
Box 2: ALTER SERVER AUDIT
Enable the server audit.
Box 3: CREATE DATABASE AUDIT
Create the database audit specification.
Box 4: FOR SERVER AUDIT
Example: The following example creates a server audit called Payrole_Security_Audit and then a database audit specification called Payrole_Security_Audit that audits SELECT and INSERT statements by the dbo user, for the HumanResources.EmployeePayHistory table in the AdventureWorks2012 database.
USE master ;
GO
-- Create the server audit.
CREATE SERVER AUDIT Payrole_Security_Audit
TO FILE ( FILEPATH =
'C:\Program Files\Microsoft SQL Server\MSSQL13.MSSQLSERVER\MSSQL\DATA' ) ; GO
-- Enable the server audit.
ALTER SERVER AUDIT Payrole_Security_Audit
WITH (STATE = ON) ;
GO
-- Move to the target database.
USE AdventureWorks2012 ;
GO
-- Create the database audit specification.
CREATE DATABASE AUDIT SPECIFICATION Audit_Pay_Tables
FOR SERVER AUDIT Payrole_Security_Audit
ADD (SELECT , INSERT
ON HumanResources.EmployeePayHistory BY dbo )
WITH (STATE = ON) ;
GO
References: https://docs.microsoft.com/en-us/sql/t-sql/statements/create-database-audit- specification-transact-sql?view=sql-server-2017
NEW QUESTION: 3
深層学習モデルを開発して、半構造化、非構造化、および構造化データ型を分析しています。
モデル構築に使用できる次のデータがあります。
*スポーツイベントのビデオ録画
*イベントに関するラジオ解説の転写
*スポーツイベント中にキャプチャされた関連ソーシャルメディアフィードからのログ
モデルを作成するための環境を選択する必要があります。
どの環境を使用する必要がありますか？
A. Azure Cognitive Services
B. Azure Data Lake Analytics
C. Spark MLibを使用したAzure HDInsight
D. Azure Machine Learning Studio
Answer: A
Explanation:
Explanation
Azure Cognitive Services expand on Microsoft's evolving portfolio of machine learning APIs and enable developers to easily add cognitive features - such as emotion and video detection; facial, speech, and vision recognition; and speech and language understanding - into their applications. The goal of Azure Cognitive Services is to help developers create applications that can see, hear, speak, understand, and even begin to reason. The catalog of services within Azure Cognitive Services can be categorized into five main pillars - Vision, Speech, Language, Search, and Knowledge.
References:
https://docs.microsoft.com/en-us/azure/cognitive-services/welcome
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