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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
Certificate Validity Period:	3 Years
Exam Price:	$250 USD
Exam Duration:	90 minutes
Passing Score:	63%
Available Languages:	English
Exam Format:	Multiple Response, Multiple Choice, Scenario-based
Real Exam Qty:	63
Related Certifications:	IBM Certified Data Engineer - Cloud Pak for Data IBM Certified Administrator - Cloud Pak for Data IBM Certified Analyst - Cloud Pak for Data
Sample Questions:	IBM C1000-173 Sample Questions
Exam Way:	Online proctored or at authorized Pearson VUE test centers
Pre Condition:	No formal prerequisites required, but recommend having prior experience with IBM Cloud Pak for Data administration, Red Hat OpenShift Container Platform, and general data architecture principles.
Official Syllabus URL:	https://www.ibm.com/certify/exam?id=173

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IBM C1000-173 Exam Syllabus Topics:

Topic	Details
Topic 1	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 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 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 4	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 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.

IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q66-Q71):

NEW QUESTION # 66
When planning the integration of IBM Cloud Pak for Data with existing enterprise systems, which aspect is crucial for ensuring seamless connectivity and data exchange? (Select two)

A. API compatibility
B. Data encryption standards
C. Network bandwidth
D. User authentication mechanisms

Answer: A,C

NEW QUESTION # 67
Which statement is true about governing data lakes in IBM Knowledge Catalog?

A. It automates data discovery and provides access to enterprise data through virtualization.
B. It relies on manual processes for accessing enterprise data.
C. It increases the time and effort required for data discovery and cataloging.
D. All data is masked with no user intervention.

Answer: A

Explanation:
Within IBM Knowledge Catalog as part of IBM Cloud Pak for Data, governing data lakes is enabled via integration with Data Virtualization. This approach supports automated data discovery, cataloging, tagging, and virtualization, allowing users to access enterprise data virtually-without physical movement. Policies and governance metadata are applied automatically to virtualized assets, enabling secure and efficient data consumption. Manual processes are not required for discovery, and data is masked selectively based on policies-not completely masked without user intervention. Thus automation and virtualization are central, making statement B correct.

NEW QUESTION # 68
After importing IBM Knowledge Accelerator assets using an API endpoint, what change must be made before the assets can be used by the appropriate users?

A. Ensure the user permission role is active.
B. Add collaborators to the Knowledge Accelerators categories.
C. Ensure a shared credential has been configured.
D. Add users to the Knowledge Accelerators security group.

Answer: B

Explanation:
After importing IBM Knowledge Accelerator (KA) assets using an API (or other methods), those assets -- such as categories, terms, and relationships -- are part of governance artifacts in Cloud Pak for Data. However, to make them usable by specific users, you must assign collaborators to the relevant categories.
This ensures users have the appropriate permissions (e.g., to view, curate, or manage terms) within the Information Governance Catalog (IGC) or Watson Knowledge Catalog.

NEW QUESTION # 69
What are two ways to customize Knowledge Accelerators to meet specific requirements?

A. Create a separate project for any customized content.
B. Customize the content in a separate namespace.
C. Place Knowledge Accelerator content in a "development" vocabulary separate from the main stream "enterprise vocabulary".
D. Use a GitHub Repo to manage any changes.
E. Change Knowledge Accelerator content inline.

Answer: A,C

Explanation:
Customization of Knowledge Accelerators in IBM Cloud Pak for Data is a structured process to preserve the integrity of base content while allowing for extension. The recommended approaches include:
Creating a separate project for customizations, so that changes are isolated and easily managed without affecting the source accelerator.
Using a "development" vocabulary where custom terms and structures are created. This is separate from the "enterprise vocabulary," which contains the unmodified, original Knowledge Accelerator content. Inline editing of the original content is discouraged. Use of GitHub or namespaces is not part of the official customization workflow.

NEW QUESTION # 70
Which container orchestration platform is used by IBM Cloud Pak for Data?

A. Docker Swarm
B. Docker
C. Kubernetes
D. OpenShift

Answer: D

Explanation:
IBM Cloud Pak for Data is built on OpenShift, which is an enterprise Kubernetes platform.
OpenShift provides a secure and scalable platform for managing containerized applications, including those within Cloud Pak for Data.

NEW QUESTION # 71
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