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IBM C1000-173 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Architect with Data Source Services: This domain measures expertise of a Data Integration Architect and includes architecting solutions with data replication technologies to synchronize data across systems. IBM Data Virtualization architecture enables access to and querying of disparate data sources without data movement. Architecting with watsonx.data focuses on building intelligent data lakes and query engines. Architecting with Db2-related services involves designing scalable data management and processing architectures using IBM's Db2 platforms.
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
  • Architect with AI Series: This section measures the skills of an AI Solution Architect and includes designing architectures for solutions involving various IBM Watson AI services. Architecting with Watson Assistant involves creating conversational AI interfaces. Watson Discovery solutions focus on building cognitive search and content analytics applications. Watson Pipelines solutions involve orchestrating data science workflows. Watson OpenScale architectures enable AI model monitoring and governance. Architecting with Match 360 supports personalized engagement by integrating multi-channel customer insights.

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q79-Q84):

NEW QUESTION # 79
An organization has created an extensive number of data protection rules as part of their Cloud Pak for Data implementation. The governance team is working on developing best practices for their team to maximize this investment.
Which service can be used to create a copy of cataloged asset data with all data protection rules applied?

Answer: C


NEW QUESTION # 80
How does IBM Cloud Pak for Data support disaster recovery and business continuity planning?

Answer: A


NEW QUESTION # 81
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 # 82
How does the IBM Data Virtualization service virtualize files in shared directories?

Answer: A

Explanation:
To virtualize files that reside in shared directories (e.g., NFS, SMB, or other on-premises sources), IBM Data Virtualization uses a remote connector agent. This remote connector is installed and executed on the source server to enable secure access and metadata extraction. The service does not scan networks automatically nor rely on FTP. Directly adding file shares via the UI is not sufficient without the backend connector in place, which acts as a secure communication bridge.


NEW QUESTION # 83
Insurance industry datasets frequently include personally identifiable information (PII) and many data analysts need access to datasets but not to PII.
Which Cloud Pak for Data services leverage Data Protection Rules?

Answer: A

Explanation:
IBM Cloud Pak for Data includes built-in Data Protection Rules to enforce access control on sensitive data, such as PII. These rules are integrated directly into services like IBM Data Virtualization, Data Privacy, and IBM Knowledge Catalog. When analysts or applications access data through these services, the platform automatically masks, obfuscates, or restricts access to sensitive fields based on the defined policies. This ensures compliance with data privacy regulations and organizational security policies without manual intervention.


NEW QUESTION # 84
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