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IBM C1000-173 Exam Syllabus Topics:

Topic	Details
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 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.
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.
Topic 4	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.
Topic 5	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.

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q82-Q87):

NEW QUESTION # 82
What outcomes can be achieved from Match 360?

A. Produces a AI based dashboard to let users analyze business data.
B. Uses a dialog format to talk with your data to get insights.
C. Connect disparate data sources to provide a virtual view of your data.
D. Produces statistics and graphs to let users analyze and explore master data.

Answer: D

Explanation:
Match 360 is IBM's master data management (MDM) service integrated into Cloud Pak for Data. It produces master data views along with statistics, graphs, and insights that allow users to explore, analyze, and understand their master data entities (e.g., customers, products). While it does integrate data from disparate sources, its focus is on consolidating and providing master data analysis rather than virtual views (B) or conversational analytics (A).

NEW QUESTION # 83
Which of the following is a key feature of IBM Cloud Pak for Data's architecture?

A. Integration with only on-premise systems
B. A containerized architecture based on Kubernetes
C. Built-in data warehousing
D. Limited integration with cloud services

Answer: B

Explanation:
IBM Cloud Pak for Data is built on a containerized architecture, leveraging Kubernetes and OpenShift. This allows the platform to be flexible, scalable, and portable across various environments, including on-premises, public clouds, and hybrid clouds.

NEW QUESTION # 84
How does IBM Cloud Pak for Data support disaster recovery and business continuity planning?

A. By providing automated backup and restore capabilities
B. All of the above
C. By enabling cross-region data replication
D. By supporting high-availability cluster configurations

Answer: B

NEW QUESTION # 85
How does the integration of security with the platform benefit Data Replication on Cloud Pak for Data?

A. Compromises data integrity
B. Ensures secure data transfer and access
C. Enhances the risk of data breaches
D. Reduces compliance with industry standards

Answer: B

NEW QUESTION # 86
Which mechanism will ensure long term system stability of a Cloud Pak for Data environment?

A. Add more worker nodes.
B. Enforce quotas to specify the maximum amount of memory and vCPU for the platform, a specific service, or a project.
C. Adjust the data throttle property on a per user basis to limit data throughput to available resources.
D. Setup pod autoscaling to set a resource limit for all Cloud Pak for Data service pods.

Answer: B

NEW QUESTION # 87
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