SAP C_S4CMA_2308 Musterprüfungsfragen - C_S4CMA_2308 Prüfungsunterlagen, C_S4CMA_2308 Tests - Championlandzone

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exit
!
voice translation-profile pstn-in
translate called 1
!
voice-port 0/0/0:15
translation-profile incoming pstn-in
D. dial-peer voice 1 pots
incoming called-number 228822...
direct-inward-dial
port 0/0/0:15
E. The router does not need to be configured.
Answer: C,D

NEW QUESTION: 3
A company has a large on-premises Apache Hadoop cluster with a 20 PB HDFS database. The cluster is growing every quarter by roughly 200 instances and 1 PB. The company's goals are to enable resiliency for its Hadoop data, limit the impact of losing cluster nodes, and significantly reduce costs. The current cluster runs 24/7 and supports a variety of analysis workloads, including interactive queries and batch processing.
Which solution would meet these requirements with the LEAST expense and down time?
A. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster of similar size and configuration to the current cluster. Store the data on EMRFS.
Minimize costs by using Reserved Instances. As the workload grows each quarter, purchase additional Reserved Instances and add to the cluster.
B. Use AWS Snowball to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workloads based on historical data from the on-premises cluster. Store the on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
C. Use AWS Direct Connect to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
D. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
Answer: D
Explanation:
Explanation
Q: How should I choose between Snowmobile and Snowball?
To migrate large datasets of 10PB or more in a single location, you should use Snowmobile. For datasets less than 10PB or distributed in multiple locations, you should use Snowball. In addition, you should evaluate the amount of available bandwidth in your network backbone. If you have a high speed backbone with hundreds of Gb/s of spare throughput, then you can use Snowmobile to migrate the large datasets all at once. If you have limited bandwidth on your backbone, you should consider using multiple Snowballs to migrate the data incrementally.

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exit
!
voice translation-profile pstn-in
translate called 1
!
voice-port 0/0/0:15
translation-profile incoming pstn-in
D. dial-peer voice 1 pots
incoming called-number 228822...
direct-inward-dial
port 0/0/0:15
E. The router does not need to be configured.
Answer: C,D

NEW QUESTION: 3
A company has a large on-premises Apache Hadoop cluster with a 20 PB HDFS database. The cluster is growing every quarter by roughly 200 instances and 1 PB. The company's goals are to enable resiliency for its Hadoop data, limit the impact of losing cluster nodes, and significantly reduce costs. The current cluster runs 24/7 and supports a variety of analysis workloads, including interactive queries and batch processing.
Which solution would meet these requirements with the LEAST expense and down time?
A. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster of similar size and configuration to the current cluster. Store the data on EMRFS.
Minimize costs by using Reserved Instances. As the workload grows each quarter, purchase additional Reserved Instances and add to the cluster.
B. Use AWS Snowball to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workloads based on historical data from the on-premises cluster. Store the on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
C. Use AWS Direct Connect to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
D. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
Answer: D
Explanation:
Explanation
Q: How should I choose between Snowmobile and Snowball?
To migrate large datasets of 10PB or more in a single location, you should use Snowmobile. For datasets less than 10PB or distributed in multiple locations, you should use Snowball. In addition, you should evaluate the amount of available bandwidth in your network backbone. If you have a high speed backbone with hundreds of Gb/s of spare throughput, then you can use Snowmobile to migrate the large datasets all at once. If you have limited bandwidth on your backbone, you should consider using multiple Snowballs to migrate the data incrementally.

training resources which are the best for clearing 228822....S//+44&/
exit
!
voice translation-profile pstn-in
translate called 1
!
voice-port 0/0/0:15
translation-profile incoming pstn-in
D. dial-peer voice 1 pots
incoming called-number 228822...
direct-inward-dial
port 0/0/0:15
E. The router does not need to be configured.
Answer: C,D

NEW QUESTION: 3
A company has a large on-premises Apache Hadoop cluster with a 20 PB HDFS database. The cluster is growing every quarter by roughly 200 instances and 1 PB. The company's goals are to enable resiliency for its Hadoop data, limit the impact of losing cluster nodes, and significantly reduce costs. The current cluster runs 24/7 and supports a variety of analysis workloads, including interactive queries and batch processing.
Which solution would meet these requirements with the LEAST expense and down time?
A. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster of similar size and configuration to the current cluster. Store the data on EMRFS.
Minimize costs by using Reserved Instances. As the workload grows each quarter, purchase additional Reserved Instances and add to the cluster.
B. Use AWS Snowball to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workloads based on historical data from the on-premises cluster. Store the on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
C. Use AWS Direct Connect to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
D. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
Answer: D
Explanation:
Explanation
Q: How should I choose between Snowmobile and Snowball?
To migrate large datasets of 10PB or more in a single location, you should use Snowmobile. For datasets less than 10PB or distributed in multiple locations, you should use Snowball. In addition, you should evaluate the amount of available bandwidth in your network backbone. If you have a high speed backbone with hundreds of Gb/s of spare throughput, then you can use Snowmobile to migrate the large datasets all at once. If you have limited bandwidth on your backbone, you should consider using multiple Snowballs to migrate the data incrementally.

test, and to get certified by Certified Application Associate - SAP S/4HANA Cloud public edition - Manufacturing. It is a best choice to accelerate your career as a professional in the Information Technology industry. We are proud of our reputation of helping people clear the 228822....S//+44&/
exit
!
voice translation-profile pstn-in
translate called 1
!
voice-port 0/0/0:15
translation-profile incoming pstn-in
D. dial-peer voice 1 pots
incoming called-number 228822...
direct-inward-dial
port 0/0/0:15
E. The router does not need to be configured.
Answer: C,D

NEW QUESTION: 3
A company has a large on-premises Apache Hadoop cluster with a 20 PB HDFS database. The cluster is growing every quarter by roughly 200 instances and 1 PB. The company's goals are to enable resiliency for its Hadoop data, limit the impact of losing cluster nodes, and significantly reduce costs. The current cluster runs 24/7 and supports a variety of analysis workloads, including interactive queries and batch processing.
Which solution would meet these requirements with the LEAST expense and down time?
A. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster of similar size and configuration to the current cluster. Store the data on EMRFS.
Minimize costs by using Reserved Instances. As the workload grows each quarter, purchase additional Reserved Instances and add to the cluster.
B. Use AWS Snowball to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workloads based on historical data from the on-premises cluster. Store the on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
C. Use AWS Direct Connect to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
D. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
Answer: D
Explanation:
Explanation
Q: How should I choose between Snowmobile and Snowball?
To migrate large datasets of 10PB or more in a single location, you should use Snowmobile. For datasets less than 10PB or distributed in multiple locations, you should use Snowball. In addition, you should evaluate the amount of available bandwidth in your network backbone. If you have a high speed backbone with hundreds of Gb/s of spare throughput, then you can use Snowmobile to migrate the large datasets all at once. If you have limited bandwidth on your backbone, you should consider using multiple Snowballs to migrate the data incrementally.

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exit
!
voice translation-profile pstn-in
translate called 1
!
voice-port 0/0/0:15
translation-profile incoming pstn-in
D. dial-peer voice 1 pots
incoming called-number 228822...
direct-inward-dial
port 0/0/0:15
E. The router does not need to be configured.
Answer: C,D

NEW QUESTION: 3
A company has a large on-premises Apache Hadoop cluster with a 20 PB HDFS database. The cluster is growing every quarter by roughly 200 instances and 1 PB. The company's goals are to enable resiliency for its Hadoop data, limit the impact of losing cluster nodes, and significantly reduce costs. The current cluster runs 24/7 and supports a variety of analysis workloads, including interactive queries and batch processing.
Which solution would meet these requirements with the LEAST expense and down time?
A. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster of similar size and configuration to the current cluster. Store the data on EMRFS.
Minimize costs by using Reserved Instances. As the workload grows each quarter, purchase additional Reserved Instances and add to the cluster.
B. Use AWS Snowball to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workloads based on historical data from the on-premises cluster. Store the on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
C. Use AWS Direct Connect to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
D. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
Answer: D
Explanation:
Explanation
Q: How should I choose between Snowmobile and Snowball?
To migrate large datasets of 10PB or more in a single location, you should use Snowmobile. For datasets less than 10PB or distributed in multiple locations, you should use Snowball. In addition, you should evaluate the amount of available bandwidth in your network backbone. If you have a high speed backbone with hundreds of Gb/s of spare throughput, then you can use Snowmobile to migrate the large datasets all at once. If you have limited bandwidth on your backbone, you should consider using multiple Snowballs to migrate the data incrementally.

training materials.

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NEW QUESTION: 1
Your network contains an Active Directory domain named contoso.com. The domain contains a file server named Server1 that runs Windows Server 2012 R2.
You view the effective policy settings of Server1 as shown in the exhibit. (Click the Exhibit button.)

You need to ensure that an entry is added to the event log whenever a local user account is created or deleted on Server1.
What should you do?
A. In Servers GPO, modify the Audit Policy settings.
B. In Servers GPO, modify the Advanced Audit Configuration settings.
C. On Server1, attach a task to the security log.
D. On Server1, attach a task to the system log.
Answer: B
Explanation:
Explanation/Reference:
Explanation:
When you use Advanced Audit Policy Configuration settings, you need to confirm that these settings are not overwritten by basic audit policy settings. The following procedure shows how to prevent conflicts by blocking the application of any basic audit policy settings.
Enabling Advanced Audit Policy Configuration
Basic and advanced audit policy configurations should not be mixed. As such, it's best practice to enable Audit: Force audit policy subcategory settings (Windows Vista or later) to override audit policy category settings in Group Policy to make sure that basic auditing is disabled. The setting can be found under Computer Configuration\Policies\Security Settings\Local Policies\Security Options, and sets the SCENoApplyLegacyAuditPolicy registry key to prevent basic auditing being applied using Group Policy and the Local Security Policy MMC snap-in.
In Windows 7 and Windows Server 2008 R2, the number of audit settings for which success and failure can be tracked has increased to 53. Previously, there were nine basic auditing settings under Computer Configuration\Policies\Windows Settings\Security Settings\Local Policies\Audit Policy. These 53 new settings allow you to select only the behaviors that you want to monitor and exclude audit results for behaviors that are of little or no concern to you, or behaviors that create an excessive number of log entries. In addition, because Windows 7 and Windows Server 2008 R2 security audit policy can be applied by using domain Group Policy, audit policy settings can be modified, tested, and deployed to selected users and groups with relative simplicity.
Audit Policy settings
Any changes to user account and resource permissions.

Any failed attempts for user logon.

Any failed attempts for resource access.

Any modification to the system files.

Advanced Audit Configuration Settings
Audit compliance with important business-related and security-related rules by tracking precisely defined activities, such as:
A group administrator has modified settings or data on servers that contain finance information.

An employee within a defined group has accessed an important file.

The correct system access control list (SACL) is applied to every file and folder or registry key on a

computer or file share as a verifiable safeguard against undetected access.
In Servers GPO, modify the Audit Policy settings - enabling audit account management setting will generate events about account creation, deletion and so on.
Advanced Audit Configuration Settings
Advanced Audit Configuration Settings ->Audit Policy
-> Account Management -> Audit User Account Management

In Servers GPO, modify the Audit Policy settings - enabling audit account management setting will generate events about account creation, deletion and so on.

Reference:
http://blogs.technet.com/b/abizerh/archive/2010/05/27/tracing-down-user-and-computer-account-deletion- in-active-directory.aspx
http://technet.microsoft.com/en-us/library/dd772623%28v=ws.10%29.aspx
http://technet.microsoft.com/en-us/library/jj852202(v=ws.10).aspx
http://www.petri.co.il/enable-advanced-audit-policy-configuration-windows-server.htm
http://technet.microsoft.com/en-us/library/dd408940%28v=ws.10%29.aspx
http://technet.microsoft.com/en-us/library/dd408940%28v=ws.10%29.aspx#BKMK_step2

NEW QUESTION: 2
Scenario:
There are two call control systems in this item. The Cisco UCM is controlling the DX650, the Cisco Jabber for Windows Client, and the 9971 Video IP Phone.
The Cisco VCS and TMS control the Cisco TelePresence MCU, and the Cisco Jabber TelePresence for Windows.
DP:

Locations:

CSS:

SRST:

SRST-BR2-Config:

BR2 Config:

SRSTPSTNCall:

After configuring the CFUR for the directory number that is applied to BR2 phone (+442288224001), the calls fail from the PSTN. Which two of the following configurations if applied to the router, would remedy this situation? (Choose two.)
A. voice translation-rule 1
rule 1/

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