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IBM C1000-173 Exam Syllabus Topics:

SectionWeightObjectives
Data Virtualization, Governance, and Analytic Integration10%- Data Governance and Quality
  • 1. Understand the purpose of data governance (Steward, Catalog)
  • 2. Integrate with data fabric and knowledge graph concepts
- Manage data sources and virtualization
  • 1. Configure connections to databases and data warehouses
  • 2. Create and manage virtualized tables
Security15%- Implement security best practices
  • 1. Understand compliance and auditing requirements
  • 2. Manage secrets and encryption at rest
  • 3. Configure security context constraints (SCCs)
Administration and Monitoring15%- User and access management
  • 1. Manage users, groups, and role-based access control (RBAC)
  • 2. Integrate with external identity providers (LDAP/SAML)
- Monitor and maintain the environment
  • 1. Troubleshoot common pod and service failures
  • 2. Use OpenShift monitoring tools and CP4D logging
Planning and Designing a Cloud Pak for Data Solution20%- Plan network and storage infrastructure
  • 1. Determine storage class requirements (File, Block, Object)
  • 2. Design network policies and routes
  • 3. Plan for high availability and disaster recovery
- Size the environment
  • 1. Select appropriate OpenShift cluster configurations
  • 2. Calculate resource requirements based on user load and services
Installation and Configuration20%- Add and configure services
  • 1. Manage version upgrades of the platform and services
  • 2. Install and configure core add-on services (e.g., Data Virtualization, Watson Studio)
- Install Cloud Pak for Data on Red Hat OpenShift
  • 1. Configure the ZenService and internal authentication
  • 2. Use the IBM Cloud Pak for Data installer and operators
  • 3. Manage certificates and security settings
Cloud Pak for Data Architecture20%- Describe deployment models and licensing
  • 1. Differentiate between self-managed and cloud-managed deployments
  • 2. Understand subscription models and capacity requirements
- Explain the Cloud Pak for Data architecture, key components, and services
  • 1. Explain the integration with Red Hat OpenShift Container Platform
  • 2. Understand how services are deployed as pods in the OpenShift cluster
  • 3. Describe the purpose of Zen Core, Redis, and Postgres

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q65-Q70):

NEW QUESTION # 65
Which container orchestration platform is used by IBM Cloud Pak for Data?

Answer: B

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 # 66
What scenario best illustrates the effective use of Db2 Graph services?

Answer: D


NEW QUESTION # 67
In Watson Discovery, what is the primary purpose of using query enrichment with machine learning models?

Answer: D


NEW QUESTION # 68
What is the primary purpose of IBM Cloud Pak for Data?

Answer: A

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 # 69
What can be used to deliver business-ready data to feed AI and analytics projects?

Answer: C

Explanation:
IBM Knowledge Catalog is the core governance and cataloging service within Cloud Pak for Data that enables the delivery of trusted, business-ready data to AI and analytics pipelines. It provides data lineage, metadata management, access policies, and quality scores, ensuring data consumers use curated and compliant data. Watson Machine Learning and its accelerator are focused on model training and inference, while IBM Data Catalog is a former term replaced by Knowledge Catalog in recent versions.


NEW QUESTION # 70
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