C1000-173 Free Study Material, C1000-173 Interactive Practice Exam

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IBM C1000-173 Exam Syllabus Topics:

SectionWeightObjectives
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. Manage certificates and security settings
  • 2. Use the IBM Cloud Pak for Data installer and operators
  • 3. Configure the ZenService and internal authentication
Security15%- Implement security best practices
  • 1. Manage secrets and encryption at rest
  • 2. Understand compliance and auditing requirements
  • 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. Use OpenShift monitoring tools and CP4D logging
  • 2. Troubleshoot common pod and service failures
Data Virtualization, Governance, and Analytic Integration10%- Data Governance and Quality
  • 1. Integrate with data fabric and knowledge graph concepts
  • 2. Understand the purpose of data governance (Steward, Catalog)
- Manage data sources and virtualization
  • 1. Create and manage virtualized tables
  • 2. Configure connections to databases and data warehouses
Planning and Designing a Cloud Pak for Data Solution20%- Size the environment
  • 1. Select appropriate OpenShift cluster configurations
  • 2. Calculate resource requirements based on user load and services
- 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
Cloud Pak for Data Architecture20%- Explain the Cloud Pak for Data architecture, key components, and services
  • 1. Understand how services are deployed as pods in the OpenShift cluster
  • 2. Explain the integration with Red Hat OpenShift Container Platform
  • 3. Describe the purpose of Zen Core, Redis, and Postgres
- Describe deployment models and licensing
  • 1. Understand subscription models and capacity requirements
  • 2. Differentiate between self-managed and cloud-managed deployments

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q177-Q182):

NEW QUESTION # 177
Which type of search allows Watson Discovery to find the most relevant material in documents?

Answer: D

Explanation:
Watson Discovery employs advanced natural language processing and ranking algorithms that begin with keyword-based search. This type of search enables the tool to locate and return the most relevant document passages based on the presence and context of keywords in user queries. While it may also use metadata filters (facets), the core retrieval method remains keyword-driven to find relevance at both document and passage levels.


NEW QUESTION # 178
Which features of the IBM Knowledge Catalog service are unavailable with the Data Governance Express offering?

Answer: D

Explanation:
IBM Knowledge Catalog's Data Governance Express offering is a lightweight configuration meant for streamlined governance needs. It includes core capabilities like cataloging and basic lineage but does not support advanced metadata export or full-scale lineage visualization and tracking features. These advanced features are only available in the full IBM Knowledge Catalog service.
The Express tier is designed for simpler use cases and quicker onboarding with limited governance overhead.


NEW QUESTION # 179
Why is data replication crucial for real-time data changes?

Answer: A


NEW QUESTION # 180
Which two Cloud Pak for Data services implement data masking to support secure data sharing?

Answer: C,E

Explanation:
Data masking in IBM Cloud Pak for Data is primarily supported by IBM Knowledge Catalog and Data Privacy services. IBM Knowledge Catalog enforces masking through Data Protection Rules, which dynamically mask sensitive fields when data is accessed through virtualized connections.
Data Privacy allows creating masking flows and rules that transform datasets while maintaining usability for analytics, ensuring sensitive data is hidden or obfuscated. DataStage and Db2 Data Gate are ETL and data replication tools, respectively, and SPSS is an analytics tool, none of which natively implement comprehensive masking as a core capability.


NEW QUESTION # 181
In the context of Cloud Pak for Data and OpenShift, what is the advantage of containerization for service availability?

Answer: D


NEW QUESTION # 182
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