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IBM C1000-173 Exam Syllabus Topics:

SectionWeightObjectives
Security and Compliance Architecture22%- Plan certificate management and secure communications
- Design identity and access management
- Secure data exchange and integration
- Implement auditing and compliance controls
Architect with Data Governance Services20%- Design knowledge catalog and data discovery solutions
- Implement data privacy and regulatory compliance architectures
- Leverage knowledge accelerators and governance frameworks
Operational Readiness and Scalability15%- Design monitoring, logging and operational processes
- Plan for scalability, performance and lifecycle management
Plan for a Cloud Pak for Data Implementation25%- Plan backup, restore, high availability and disaster recovery
- Design for multi-tenancy and migration
- Size and design OpenShift/Kubernetes infrastructure
- Assess requirements and select appropriate services
Architect with Data Source and Integration Services18%- Implement data virtualization solutions
- Architect with watsonx.data and Db2 services
- Design data replication and integration architectures

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q72-Q77):

NEW QUESTION # 72
What makes a multi-engine architecture advantageous in watsonx.data?

Answer: D


NEW QUESTION # 73
What is the significance of understanding storage classes in Watson OpenScale?

Answer: B


NEW QUESTION # 74
Which plug-in is used by the Cloud Pak for Data Audit Logging service to forward audit records to a SIEM system?

Answer: B

Explanation:
The Audit Logging service in IBM Cloud Pak for Data uses Fluentd as the core log forwarding mechanism. Fluentd output plug-ins are configured to route audit logs to external SIEM systems such as Splunk or QRadar. These plug-ins are versatile and support multiple formats and transport protocols. Other options listed--like Logstash, OSS/J, or Kafka--are not the designated default forwarding mechanisms used within the CP4D Audit Logging architecture.


NEW QUESTION # 75
How are caches defined in IBM Data Virtualization?

Answer: D

Explanation:
In IBM Data Virtualization, caches must be manually defined by administrators. While monitoring and query performance statistics can guide where caching would be beneficial, the creation and configuration of caches (e.g., refresh schedules and scope) are manual tasks. There is no automated cache creation mechanism (A), nor are DataStage flows used for cache maintenance (B). Suggestions based on statistics (D) may assist administrators, but they do not automatically create the caches.


NEW QUESTION # 76
Which Cloud Pak for Data service is used to cleanse and shape tabular data?

Answer: A

Explanation:
Data Refinery is the dedicated data preparation service in IBM Cloud Pak for Data. It enables users to cleanse, shape, filter, and enrich tabular datasets through a graphical interface. Users can create data preparation flows that integrate seamlessly with Watson Studio and other services. Data Manager and Data Wrangler are not services available in CP4D, and Watson Data is not a recognized component. Data Refinery is the officially supported tool for this purpose.


NEW QUESTION # 77
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