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IBM C1000-173 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Plan for a Cloud Pak for Data Implementation: This section of the exam measures the skills of an Implementation Consultant and covers determining which Cloud Pak for Data services to deploy based on organizational needs. It involves sizing the Kubernetes
  • OpenShift cluster appropriately for workload demands and planning backup and restore strategies to ensure data protection. Planning for high availability and disaster recovery is essential to maintain uninterrupted service. Multi-tenancy requirements must be understood to support multiple user groups securely on shared infrastructure. Migration requirements need assessment to transition existing data and workloads smoothly.
Topic 2
  • Architect with Analytic Services: This domain targets a Data Analytics Architect and focuses on designing solutions using analytic components of Cloud Pak for Data. Architecting with DataStage involves creating data integration and ETL pipelines. Data Refinery architectures prepare and cleanse data for analysis. Db2 Big SQL solutions address querying large distributed data sets with SQL, facilitating analytics across diverse data sources.
Topic 3
  • Security Requirements: This domain targets a Security Architect and focuses on planning security for a Cloud Pak for Data deployment. It includes managing certificates that secure communications, identity management systems, and access and authorization controls to enforce secure and compliant user and service interactions. The auditing features and their integration with enterprise audit systems are crucial to ensure traceability and accountability. Asset interchange security involves safeguarding data movement between services.

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q88-Q93):

NEW QUESTION # 88
How does watsonx.data provide data sharing between Db2 Warehouse, Netezza, and any other data management solution?

Answer: B

Explanation:
watsonx.data uses Apache Iceberg tables as the open table format for data sharing across platforms like Db2 Warehouse, Netezza, and other compatible data management solutions.
Iceberg provides a transactional and schema-evolution-friendly table layer, allowing multiple engines to read and write data concurrently. This approach avoids proprietary loaders or simple file transfers and ensures efficient interoperability between different systems.


NEW QUESTION # 89
How does Watson Discovery support effective knowledge management in an enterprise?

Answer: C


NEW QUESTION # 90
Which plug-in is used by the Cloud Pak for Data Audit Logging service to forward audit records to a SIEM system?

Answer: A

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 # 91
How does Watson Assistant support voice interaction?

Answer: C


NEW QUESTION # 92
How can multi-tenancy be achieved with multiple instances of Cloud Pak for Data?

Answer: D


NEW QUESTION # 93
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