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IBM C1000-173 Exam Syllabus Topics:

SectionObjectives
Topic 1: Cloud Pak for Data Architecture Overview- Deployment architectures and environments
- CP4D core platform components and services
Topic 2: AI and Machine Learning Lifecycle- Model development, training, and deployment workflows
- Watson Studio project lifecycle
Topic 3: Data Storage and Virtualization- Data Virtualization services and query federation
- Db2 and integrated storage options
Topic 4: Security, Operations, and Platform Management- Identity and access management in CP4D
- Monitoring, scaling, and operational best practices
Topic 5: Data Governance and Cataloging- Watson Knowledge Catalog concepts
- Data lineage, metadata management, and governance policies
Topic 6: Data Integration and Engineering- Data ingestion pipelines and DataStage concepts
- Data transformation and ETL/ELT workflows

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q97-Q102):

NEW QUESTION # 97
Which type of OpenShift route configuration supports client certificate authentication?

Answer: C

Explanation:
Passthrough route configuration on OpenShift is the only route type that preserves the original TLS connection from the client to the backend service. This is essential for supporting client certificate authentication, as the certificate must be passed directly to the application without termination or inspection at the router level. Edge and Re-encrypt routes terminate the TLS connection at the OpenShift router or re- encrypt it with a new certificate, making them unsuitable for mutual TLS (mTLS) or client certificate scenarios.


NEW QUESTION # 98
Which statement describes MPP (Massively Parallel Processing) Database architecture?

Answer: D

Explanation:
MPP, or Massively Parallel Processing, is a database architecture model where data is divided and processed across multiple compute nodes in parallel. Each node works independently on a portion of the data, dramatically improving query performance and throughput for analytics workloads. This model is ideal for big data and analytical queries, not transactional workloads. It differs from shared-disk models or replication strategies like two-phase commit. The correct definition involves distributed data and parallel query execution, as described in option C.


NEW QUESTION # 99
In a multi-tenant Cloud Pak for Data environment, which aspects are critical to ensure efficient resource allocation and isolation?

Answer: B,C,D


NEW QUESTION # 100
Which two Cloud Pak for Data services support the multi-tenancy mechanism of installing the service once and provisioning the workloads in tethered projects?

Answer: A,C

Explanation:
Cloud Pak for Data supports service-level multi-tenancy by enabling some services to be installed centrally and then provisioned into user "tethered" namespaces (projects). In version 4.7, Analytics Engine (Apache Spark) and IBM Data Virtualization services support this tethered#project model: they can be installed once and then instantiated per project across multiple tenants. Core services like Db2, Cognos Analytics, and Watson Pipelines in 4.7 require installation per instance and do not yet support tethered#namespace provisioning via multi#tenant model.


NEW QUESTION # 101
The data integration team at a financial services company has always struggled to manage resources as the number of integration jobs changes throughout the month.
Which two settings are available when configuring Dynamic Workload Management for a specific DataStage instance?

Answer: B,C


NEW QUESTION # 102
......

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