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IBM C1000-173 Exam Overview:

Certification Vendor:	IBM
Exam Name:	IBM Cloud Pak for Data v4.7 Architect
Exam Number:	C1000-173
Exam Format:	Scenario-based questions, Multiple choice
Real Exam Qty:	62
Related Certifications:	IBM Certified Solution Advisor - Cloud Pak for Data IBM Certified Specialist - Cloud Pak for Data
Passing Score:	66%
Exam Duration:	90 minutes
Available Languages:	English
Exam Price:	USD 200
Certificate Validity Period:	No fixed expiration
Recommended Training:	Solution Architect: IBM Cloud Pak for Data v4.x IBM Cloud Pak for Data Architecture and Implementation
Exam Registration:	Pearson VUE IBM Certification Registration
Sample Questions:	IBM C1000-173 Sample Questions
Exam Way:	Online proctored or onsite at authorized test centers
Pre Condition:	No mandatory prerequisites; recommended experience: 6+ months with Cloud Pak for Data, knowledge of OpenShift/Kubernetes, data architecture and governance concepts
Official Syllabus URL:	https://www.ibm.com/certify/exams/C1000-173

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IBM C1000-173 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 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	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.

IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q37-Q42):

NEW QUESTION # 37
Which Watson Pipeline component manages pipeline errors, typically used with DataStage?

A. Error Handling
B. Fault Settings
C. Default Control
D. Process Termination Window

Answer: A

Explanation:
In Watson Pipelines within IBM Cloud Pak for Data, error management is handled by the Error Handling component. This feature allows developers and pipeline administrators to define how pipeline failures are processed-whether to stop execution, continue, or trigger alternate flows. It ensures controlled behavior in response to job failures, particularly in complex ETL pipelines like those built with DataStage. Error Handling is a configurable element of pipeline orchestration and is typically used to enhance fault tolerance and control error propagation in production workflows.

NEW QUESTION # 38
What is a primary consideration when designing a multi-tenant architecture?

A. Reducing the scalability of resources
B. Data isolation between tenants
C. Ensuring data overlap between tenants
D. Ensuring data overlap between tenants

Answer: B

NEW QUESTION # 39
What is a primary advantage of using Watson Pipelines in AI solution architecture?

A. Providing end-to-end data processing automation
B. Isolating data silos
C. Reducing data integrity
D. Decreasing the transparency of data processing

Answer: A

NEW QUESTION # 40
Why is it important to differentiate between Metro-DR and Regional-DR in disaster recovery planning?

A. To uniformly apply the same strategy across all locations
B. To ensure inappropriate resource allocation
C. To tailor the DR strategy to specific business needs and geographical risks
D. To complicate the recovery process

Answer: C

NEW QUESTION # 41
An architect is working with a team to configure Dynamic Workload Management for a single DataStage instance on Cloud Pak for Data. Auto-scaling has been disabled and the maximum concurrent jobs has been set to 5. What will happen if a sixth concurrent job is executed?

A. The sixth job will fail and will need to be restarted.
B. The sixth job will queue until one of the other concurrent jobs completes.
C. The sixth job will start if resources are available and will automatic.

Answer: B

Explanation:
Queueing mechanism is in place. Since the maximum concurrent jobs are limited to 5, the sixth job will not start immediately. Instead, it will queue and wait for one of the currently running jobs to complete, making room for the sixth job to execute.

NEW QUESTION # 42
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