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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 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.
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 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.

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q21-Q26):

NEW QUESTION # 21
Comparing data replication with an ETL tool, which feature is exclusive to data replication concerning real-time data changes?

Answer: C


NEW QUESTION # 22
Which two Cloud Pak for Data services support storage class NFS?

Answer: B,E

Explanation:
IBM Cloud Pak for Data supports NFS#backed persistent volumes (RWX storage class) for services that require access to shared file storage. Among the available services, IBM Knowledge Catalog and Watson Discovery are known to support NFS storage classes in installation configuration (e.g.
"managed#nfs#storage") for persistent metadata and document storage. Other services like watsonx Assistant, Watson Knowledge Studio, and Planning Analytics use different storage mechanisms and do not necessarily support NFS shared storage in the standard CP4D 4.7 deployment.


NEW QUESTION # 23
What is the primary purpose of IBM Cloud Pak for Data?

Answer: D

Explanation:
IBM Cloud Pak for Data is an integrated data and AI platform that enables businesses to modernize their data architecture. It provides a complete solution for data management, analytics, AI, and data governance, helping organizations make data-driven decisions.


NEW QUESTION # 24
Which two Cloud Pak for Data predefined roles are used to define DataStage access?

Answer: A,C

Explanation:
In IBM Cloud Pak for Data, DataStage access is managed using predefined roles that grant specific permissions. The DataStage Developer role is explicitly designed to allow users to create and manage DataStage flows. The Data Steward role is involved in managing data access, lineage, and metadata, which supports governance aspects within DataStage projects. Business Analyst and Governance Steward roles are focused on cataloging and governance workflows, not DataStage design or execution. Reporting Administrator is not applicable in this context.


NEW QUESTION # 25
In the context of Db2 services, which two authentication methods ensure secure API access?

Answer: A,C


NEW QUESTION # 26
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