Ace Your Exam Preparation with IBM C1000-173 Exam Questions

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IBM C1000-173 Exam Syllabus Topics:

Section	Weight	Objectives
Architect with Data Source and Integration Services	18%	- Architect with watsonx.data and Db2 services - Implement data virtualization solutions - Design data replication and integration architectures
Plan for a Cloud Pak for Data Implementation	25%	- Size and design OpenShift/Kubernetes infrastructure - Design for multi-tenancy and migration - Assess requirements and select appropriate services - Plan backup, restore, high availability and disaster recovery
Architect with Data Governance Services	20%	- Leverage knowledge accelerators and governance frameworks - Implement data privacy and regulatory compliance architectures - Design knowledge catalog and data discovery solutions
Operational Readiness and Scalability	15%	- Plan for scalability, performance and lifecycle management - Design monitoring, logging and operational processes
Security and Compliance Architecture	22%	- Secure data exchange and integration - Design identity and access management - Implement auditing and compliance controls - Plan certificate management and secure communications

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q94-Q99):

NEW QUESTION # 94
Which of the following strategies are crucial for planning an effective backup and restore process in a Cloud Pak for Data environment?

A. Automated backup validation
B. Regular backup scheduling
C. Real-time data mirroring
D. Multi-region storage replication

Answer: A,B

NEW QUESTION # 95
How do Massively Parallel Processing (MPP) and Symmetric Multiprocessing (SMP) differ in a Db2 environment?

A. MPP requires a shared memory architecture, whereas SMP does not
B. MPP is less suited for complex analytical tasks compared to SMP
C. SMP is more scalable than MPP
D. MPP divides tasks among multiple processors, while SMP uses a single processor

Answer: D

NEW QUESTION # 96
Which potential problem can Watson OpenScale detect and mitigate?

A. Complex rule set
B. New data overwrites
C. Drift
D. Limited storage capacity

Answer: C

Explanation:
Watson OpenScale includes advanced monitoring capabilities for deployed AI models, including drift detection. Data drift refers to changes in input data distributions over time, which can degrade model performance. OpenScale continuously compares incoming data to the original training data to detect deviations and alert users when retraining may be required. It does not manage storage, data overwrites, or rule-based systems, making option B the only correct choice.

NEW QUESTION # 97
Which statement describes MPP (Massively Parallel Processing) Database architecture?

A. An analytics environment that improves performance by dividing the data across many nodes.
B. Two or more databases kept in sync via two-phase commit.
C. A transactional system which uses multiple nodes for maximum availability.
D. A data warehouse that needs all compute nodes to access a shared data store simultaneously.

Answer: A

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 # 98
Why is it important to differentiate between Metro-DR and Regional-DR in disaster recovery planning?

A. To uniformly apply the same strategy across all locations
B. To complicate the recovery process
C. To ensure inappropriate resource allocation
D. To tailor the DR strategy to specific business needs and geographical risks

Answer: D

NEW QUESTION # 99
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