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IBM C1000-173 Exam Syllabus Topics:

TopicDetails
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 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 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 (Q129-Q134):

NEW QUESTION # 129
What outcomes can be achieved from Match 360?

Answer: A

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 # 130
How does Watson Assistant support voice interaction?

Answer: D


NEW QUESTION # 131
An organization has created an extensive number of data protection rules as part of their Cloud Pak for Data implementation. The governance team is working on developing best practices for their team to maximize this investment. Which service can be used to create a copy of cataloged asset data with all data protection rules applied?

Answer: A


NEW QUESTION # 132
Are there any special considerations for the client to migrate existing server jobs to DataStage in Cloud Pak for Data?

Answer: B

Explanation:
Legacy DataStage server jobs are not automatically compatible with DataStage on Cloud Pak for Data, which uses a parallel engine architecture. MettleCI is the recommended tool to convert server jobs into parallel jobs before migration. This conversion allows reusability and ensures the migrated jobs can run efficiently in the CP4D environment. Direct migration without modification (option D) is not possible, and they do not migrate to Watson Pipelines (option A).


NEW QUESTION # 133
Which statement is true about governing data lakes in IBM Knowledge Catalog?

Answer: B

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 # 134
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