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The IBM C1000-173 certification exam is one of the best credentials in the modern IBM world. The IBM Cloud Pak for Data v4.7 Architect (C1000-173) certification offers a unique opportunity for beginners or experienced professionals to demonstrate their expertise and knowledge with an industry-recognized certificate. With the IBM Cloud Pak for Data v4.7 Architect (C1000-173) exam dumps, you can not only validate your skill set but also get solid proof of your proven expertise and knowledge.
| Section | Weight | Objectives |
|---|---|---|
| Plan for a Cloud Pak for Data Implementation | 25% | - Design for multi-tenancy and migration - Size and design OpenShift/Kubernetes infrastructure - Assess requirements and select appropriate services - Plan backup, restore, high availability and disaster recovery |
| Operational Readiness and Scalability | 15% | - Plan for scalability, performance and lifecycle management - Design monitoring, logging and operational processes |
| Security and Compliance Architecture | 22% | - Plan certificate management and secure communications - Secure data exchange and integration - Implement auditing and compliance controls - Design identity and access management |
| Architect with Data Governance Services | 20% | - Design knowledge catalog and data discovery solutions - Implement data privacy and regulatory compliance architectures - Leverage knowledge accelerators and governance frameworks |
| Architect with Data Source and Integration Services | 18% | - Implement data virtualization solutions - Architect with watsonx.data and Db2 services - Design data replication and integration architectures |
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NEW QUESTION # 146
Which two Cloud Pak for Data services support storage class NFS?
Answer: C,D
Explanation:
IBM Cloud Pak for Data supports NFS#backed persistent volumes (RWX storage class) for services that require access to shared file storage. Among the available services, IBM Knowledge Catalog and Watson Discovery are known to support NFS storage classes in installation configuration (e.g.
"managed#nfs#storage") for persistent metadata and document storage. Other services like watsonx Assistant, Watson Knowledge Studio, and Planning Analytics use different storage mechanisms and do not necessarily support NFS shared storage in the standard CP4D 4.7 deployment.
NEW QUESTION # 147
Which two Cloud Pak for Data services implement data masking to support secure data sharing?
Answer: B,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 # 148
Which data processing engine is used for Data Privacy Masking flows?
Answer: D
Explanation:
Data Privacy Masking flows in IBM Cloud Pak for Data utilize Apache Spark as the underlying data processing engine. Spark enables large-scale, distributed data masking operations for structured data, supporting high-performance transformations and compliance with privacy regulations. While DataStage can perform similar operations, the default and recommended engine for Data Privacy flows in CP4D is Spark.
dbt and Presto are not used for this masking functionality.
NEW QUESTION # 149
Which Db2 Big SQL component uses system resources efficiently to maximize throughput and minimize response time?
Answer: B
Explanation:
StreamThrough is a high-performance component used in Db2 Big SQL within IBM Cloud Pak for Data that is optimized to manage data streams and queries efficiently. It is designed to maximize throughput and minimize query response times by optimizing memory usage, resource allocation, and processing logic.
Unlike Hive or Analyzer, which are used for query execution and analysis, StreamThrough enables efficient pipeline execution by streamlining data handling. Scheduler is used for job timing but does not influence runtime efficiency directly. StreamThrough is purpose-built to enhance performance through optimal resource usage.
NEW QUESTION # 150
What is the default schedule for the diagnostics monitor when using the Alerting APIs?
Answer: D
Explanation:
You can use the IBM Software Hub monitoring and alerting framework to monitor the state of the platform.
You can set up events to alert when action is needed, based on thresholds that you define.
By default, IBM Software Hub is initialized with one monitor that runs every ten minutes. The diagnostic monitor records the status of deployments, StatefulSets, and persistent volume claims. It also tracks your system usage of virtual processors (vCPUs) and memory. The data that is collected can be used for analysis and to alert customers in a production environment based on set alert rules.
NEW QUESTION # 151
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