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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 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.
Topic 3
  • Architect with Data Governance Services: This section evaluates skills of a Data Governance Specialist, covering the architecture of knowledge catalogs to enable data discovery and management. Data Privacy architectures ensure compliance with regulatory requirements around data protection. Knowledge Accelerators involve designing solutions that speed up data governance processes through predefined policies and templates.

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q100-Q105):

NEW QUESTION # 100
What is the role of a "Connection" in the Cloud Pak for Data connectivity framework?

Answer: D

Explanation:
In IBM Cloud Pak for Data, a "Connection" is a configuration object that defines how to access an external data source, such as Db2, Oracle, or an S3 bucket. It does not involve moving or copying data. Instead, it acts as a reference to the external data source environment, enabling users to browse, query, and analyze the data in place. This approach supports virtualized access and governance while avoiding data duplication and ensuring data stays within its source system, aligning with enterprise data security policies.


NEW QUESTION # 101
What capability does the Watson OpenScale API provide?

Answer: C

Explanation:
Watson OpenScale focuses on the monitoring and governance of AI models. Its API allows users to programmatically measure model outcomes, track metrics like accuracy, precision, fairness, and drift, and support compliance with responsible AI practices. It does not build chat interfaces (A), manage data in Watson Studio (B), or extract answers from documents (C). These capabilities are aligned with other Watson services, but OpenScale is centered on AI governance and model performance measurement.


NEW QUESTION # 102
When migrating DataStage, what are key considerations? (Select two)

Answer: B,D


NEW QUESTION # 103
In the context of Cloud Pak for Data, what factors should be considered for accurately sizing a cluster?

Answer: A,B,C


NEW QUESTION # 104
Which two Cloud Pak for Data services implement data masking to support secure data sharing?

Answer: B,E

Explanation:
Data masking in IBM Cloud Pak for Data is primarily supported by IBM Knowledge Catalog and Data Privacy services. IBM Knowledge Catalog enforces masking through Data Protection Rules, which dynamically mask sensitive fields when data is accessed through virtualized connections.
Data Privacy allows creating masking flows and rules that transform datasets while maintaining usability for analytics, ensuring sensitive data is hidden or obfuscated. DataStage and Db2 Data Gate are ETL and data replication tools, respectively, and SPSS is an analytics tool, none of which natively implement comprehensive masking as a core capability.


NEW QUESTION # 105
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