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NEW QUESTION: 1
위험 기반 감사 전략을 개발할 때 IS 감사인은 다음을 보장하기 위해 위험 평가를 수행해야 합니다.
A. 취약점 및 위협이 식별됩니다.
B. 감사 위험이 고려됩니다.
C. 간격 분석이 적절합니다.
D. 위험을 완화하는데 필요한 컨트롤이 마련되어 있습니다.
Answer: A
Explanation:
설명:
위험 기반 감사 전략을 개발할 때 위험 요소와 취약점을 이해하는 것이 중요합니다. 이를 통해 감사 대상 영역과 범위를 결정하게 됩니다. 위험을 완화하기 위해 적절한 통제가 필요한지 이해하는 것은 결과적으로 감사의 결과입니다. 감사 위험은 감사의 고유 한 측면이며, 감사 프로세스와 직접 관련이 있으며 감사 대상 환경의 위험 분석과 관련이 없습니다. 갭 분석은 일반적으로 실제 상태를 예상되거나 바람직한 상태와 비교하는 것이 아닙니다.
NEW QUESTION: 2
In an ODI interface, can source tables be declared as not joined?
A. Yes, it is possible to create an ODI procedure to declare joins for the source tables.
B. No, in ODI, it is mandatory that all the source data stores are joined directly or indirectly.
C. Yes, ODI generates the code calculating a sample of the data, profiling it, and deciding automatically if a join exists.
D. No, by default, every added data store in the source declaration of an interface is joined with an inner join.
Answer: B
NEW QUESTION: 3
注：この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、記載された目標を達成する可能性のある独自のソリューションが含まれています。一部の質問セットには複数の正しい解決策がある場合もあれば、正しい解決策がない場合もあります。
このセクションの質問に回答すると、その質問に戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
層6〜8のセットアップモニタリングが必要です。
何を設定する必要がありますか？
A. データエンジニアにメールを送信するデータベースのCPU使用率を監視するアラートルール
B. データエンジニアに電子メールを送信するエラスティックプールのCPU割合を監視するアラートルール
C. データエンジニアにメールを送信するデータベースのストレージの割合を監視するアラートルール
D. データエンジニアにメールを送信する平均ストレージパーセンテージの拡張イベント
E. データエンジニアに電子メールを送信するエラスティックプールのストレージの割合を監視するアラートルール
Answer: E
Explanation:
Scenario:
Tiers 6 through 8 must have unexpected resource storage usage immediately reported to data engineers.
Tier 3 and Tier 6 through Tier 8 applications must use database density on the same server and Elastic pools in a cost-effective manner.
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
Your company develops an application named App1 that is deployed in production.
As part of an application update, a new service is being added to App1. The new service requires access to an application named App2 that is currently in development.
You need to ensure that you can deploy the update to App1 before App2 becomes available. You must be able to enable the service in App1 once App2 is deployed.
What should you do?
A. Implement a feature flag.
B. Create a fork in the build.
C. Implement a branch policy.
D. Create a branch in the build.
Answer: D
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