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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
  • 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 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 4
  • 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 5
  • 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.

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q139-Q144):

NEW QUESTION # 139
What is a Data Refinery flow in Cloud Pak for Data?

Answer: C

Explanation:
A Data Refinery flow is an ordered sequence of data operations applied to tabular data for preparation, cleansing, and transformation. Users can create a series of steps such as filtering, joining, aggregating, and applying custom expressions. The flow is saved and can be rerun on updated datasets to ensure consistency in data preparation. It is not a storage system (A), an ML model (B), or a visualization tool (D).


NEW QUESTION # 140
Which of the following services is NOT included in IBM Cloud Pak for Data?

Answer: C

Explanation:
IBM Cloud Pak for Data includes services like Watson Studio (for AI and data science), Watson Knowledge Catalog (for data governance), and IBM DataStage (for data integration). IBM Cloud Pak for Multicloud Management is a different solution focused on managing multiple cloud environments, not data.


NEW QUESTION # 141
In the context of Watson Assistant, what purpose do storage classes serve?

Answer: D


NEW QUESTION # 142
When granting a user access to the Data Engineer role, which two permissions will the user be associated with as part of this role?

Answer: A,C

Explanation:
The Data Engineer role in IBM Cloud Pak for Data includes permissions necessary for managing the data pipeline lifecycle. This includes the ability to create projects, manage data assets, and configure data protection rules, which are critical for ensuring data privacy and governance. The role does not include platform-level administrative privileges like managing the platform or monitoring all workloads. Workflow management is typically assigned to users with broader project or orchestrator roles.


NEW QUESTION # 143
Which of the following is a key feature of IBM Cloud Pak for Data's architecture?

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 # 144
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