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NEW QUESTION: 1
"Which of the following can benefit from SARFAESI, 2002?"
A. Both of the above
B. None of the above
C. Financial Institutions
D. Banks
Answer: A

NEW QUESTION: 2
View the Exhibit for some of the current parameter settings.

A user logs in to the HR schema and issues the following commands:
SQL> CREATE TABLE emp (empno NUMBER(3), enameVARCHAR2(20), sal NUMBER(8,2));
SQL> INSERT INTO emp(empno,ename) VALUES(1 /JAMES');
At this moment, a second user also logs in to the HR schema and issues the following command: SQL> ALTER TABLE emp MODIFY sal NUMBER(10,2);
What happens in the above scenario?
A. A deadlock is created.
B. The second user's command executes successfully.
C. The second user's session waits for a time period before producing the resource busy error.
D. The second user's session immediately produces the resource busy error.
Answer: C

NEW QUESTION: 3
You need to ensure that Azure Data Factory pipelines can be deployed. How should you configure authentication and authorization for deployments? To answer, select the appropriate options in the answer choices.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

The way you control access to resources using RBAC is to create role assignments. This is a key concept to understand - it's how permissions are enforced. A role assignment consists of three elements: security principal, role definition, and scope.
Scenario:
No credentials or secrets should be used during deployments
Phone-based poll data must only be uploaded by authorized users from authorized devices Contractors must not have access to any polling data other than their own Access to polling data must set on a per-active directory user basis References:
https://docs.microsoft.com/en-us/azure/role-based-access-control/overview
Topic 3, Litware, inc
Overview
General Overview
Litware, Inc, is an international car racing and manufacturing company that has 1,000 employees. Most employees are located in Europe. The company supports racing teams that complete in a worldwide racing series.
Physical Locations
Litware has two main locations: a main office in London, England, and a manufacturing plant in Berlin, Germany.
During each race weekend, 100 engineers set up a remote portable office by using a VPN to connect the datacentre in the London office. The portable office is set up and torn down in approximately 20 different countries each year.
Existing environment
Race Central
During race weekends, Litware uses a primary application named Race Central. Each car has several sensors that send real-time telemetry data to the London datacentre. The data is used for real-time tracking of the cars.
Race Central also sends batch updates to an application named Mechanical Workflow by using Microsoft SQL Server Integration Services (SSIS).
The telemetry data is sent to a MongoDB database. A custom application then moves the data to databases in SQL Server 2017. The telemetry data in MongoDB has more than 500 attributes. The application changes the attribute names when the data is moved to SQL Server 2017.
The database structure contains both OLAP and OLTP databases.
Mechanical Workflow
Mechanical Workflow is used to track changes and improvements made to the cars during their lifetime.
Currently, Mechanical Workflow runs on SQL Server 2017 as an OLAP system.
Mechanical Workflow has a named Table1 that is 1 TB. Large aggregations are performed on a single column of Table 1.
Requirements
Planned Changes
Litware is the process of rearchitecting its data estate to be hosted in Azure. The company plans to decommission the London datacentre and move all its applications to an Azure datacentre.
Technical Requirements
Litware identifies the following technical requirements:
* Data collection for Race Central must be moved to Azure Cosmos DB and Azure SQL Database. The data must be written to the Azure datacentre closest to each race and must converge in the least amount of time.
* The query performance of Race Central must be stable, and the administrative time it takes to perform optimizations must be minimized.
* The datacentre for Mechanical Workflow must be moved to Azure SQL data Warehouse.
* Transparent data encryption (IDE) must be enabled on all data stores, whenever possible.
* An Azure Data Factory pipeline must be used to move data from Cosmos DB to SQL Database for Race Central. If the data load takes longer than 20 minutes, configuration changes must be made to Data Factory.
* The telemetry data must migrate toward a solution that is native to Azure.
* The telemetry data must be monitored for performance issues. You must adjust the Cosmos DB Request Units per second (RU/s) to maintain a performance SLA while minimizing the cost of the Ru/s.
Data Masking Requirements
During rare weekends, visitors will be able to enter the remote portable offices. Litware is concerned that some proprietary information might be exposed. The company identifies the following data masking requirements for the Race Central data that will be stored in SQL Database:
* Only show the last four digits of the values in a column named SuspensionSprings.
* Only Show a zero value for the values in a column named ShockOilWeight.

NEW QUESTION: 4
Universal Containersの管理者は、すべてのアカウントに、そのアカウントの請求先郵便番号に基づいて請求先州/都道府県があることを確認して、データ品質を改善したいと考えています。この要件を満たすことができる2つのソリューションはどれですか。
2つの答えを選んでください。
A. 検証ルールを使用して、郵便番号を都道府県にマップするカスタムオブジェクトに請求郵便番号のHLOOKUPを実行します。
B. 郵便番号を州/省にマップするカスタムオブジェクトに基づいて、請求州/省を入力するワークフロールールを使用します。
C. 郵便番号を州/省にマップするカスタムオブジェクトに基づいて、請求州/省を生成するトリガーを使用します。
D. 検証ルールを使用して、郵便番号を都道府県にマップするカスタムオブジェクトに請求郵便番号のVLOOKUPを実行します。
Answer: C,D

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