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IBM C1000-173 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Security15%- Implement security best practices
  • 1. Manage secrets and encryption at rest
  • 2. Configure security context constraints (SCCs)
  • 3. Understand compliance and auditing requirements
Topic 2: Data Virtualization, Governance, and Analytic Integration10%- Manage data sources and virtualization
  • 1. Configure connections to databases and data warehouses
  • 2. Create and manage virtualized tables
- Data Governance and Quality
  • 1. Integrate with data fabric and knowledge graph concepts
  • 2. Understand the purpose of data governance (Steward, Catalog)
Topic 3: Administration and Monitoring15%- User and access management
  • 1. Integrate with external identity providers (LDAP/SAML)
  • 2. Manage users, groups, and role-based access control (RBAC)
- Monitor and maintain the environment
  • 1. Troubleshoot common pod and service failures
  • 2. Use OpenShift monitoring tools and CP4D logging
Topic 4: Planning and Designing a Cloud Pak for Data Solution20%- Plan network and storage infrastructure
  • 1. Determine storage class requirements (File, Block, Object)
  • 2. Plan for high availability and disaster recovery
  • 3. Design network policies and routes
- Size the environment
  • 1. Calculate resource requirements based on user load and services
  • 2. Select appropriate OpenShift cluster configurations
Topic 5: 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
Topic 6: Installation and Configuration20%- Install Cloud Pak for Data on Red Hat OpenShift
  • 1. Use the IBM Cloud Pak for Data installer and operators
  • 2. Manage certificates and security settings
  • 3. Configure the ZenService and internal authentication
- 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)

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q112-Q117):

NEW QUESTION # 112
When planning for the data management console in Db2, what functionality is crucial for effective database management?

Answer: A


NEW QUESTION # 113
How does watsonx.data provide data sharing between Db2 Warehouse, Netezza, and any other data management solution?

Answer: A

Explanation:
watsonx.data uses Apache Iceberg tables as the open table format for data sharing across platforms like Db2 Warehouse, Netezza, and other compatible data management solutions. Iceberg provides a transactional and schema-evolution-friendly table layer, allowing multiple engines to read and write data concurrently. This approach avoids proprietary loaders or simple file transfers and ensures efficient interoperability between different systems.


NEW QUESTION # 114
What is the primary goal of High Availability in computing environments?

Answer: B


NEW QUESTION # 115
An enterprise architect in a financial institute is deciding on the deployment option for Cloud Pak for Data on their existing OpenShift Container Platform cluster. They have decided to use an automated deployment option and install Cloud Pak for Data from the cloud provider's marketplace. What are the limitations they may face with this decision?

Answer: C

Explanation:
Partial installation of Cloud Pak for Data must be done manually during the first-time installation, especially when the installation is performed from the cloud provider's marketplace. Certain steps in the installation process may need to be done manually, such as the configuration of services or additional customization needed for the specific environment.


NEW QUESTION # 116
What key features should be emphasized when integrating Watson OpenScale for AI model monitoring? (Select two)

Answer: B,C


NEW QUESTION # 117
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