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IBM C1000-173 Exam Overview:

Certification Vendor:	IBM
Exam Name:	IBM Cloud Pak for Data v4.7 Architect
Exam Number:	C1000-173
Related Certifications:	IBM Certified Specialist - Cloud Pak for Data IBM Certified Solution Advisor - Cloud Pak for Data
Exam Price:	USD 200
Real Exam Qty:	62
Exam Duration:	90 minutes
Certificate Validity Period:	No fixed expiration
Exam Format:	Multiple choice, Scenario-based questions
Available Languages:	English
Passing Score:	66%
Recommended Training:	Solution Architect: IBM Cloud Pak for Data v4.x IBM Cloud Pak for Data Architecture and Implementation
Exam Registration:	Pearson VUE IBM Certification Registration
Sample Questions:	IBM C1000-173 Sample Questions
Exam Way:	Online proctored or onsite at authorized test centers
Pre Condition:	No mandatory prerequisites; recommended experience: 6+ months with Cloud Pak for Data, knowledge of OpenShift/Kubernetes, data architecture and governance concepts
Official Syllabus URL:	https://www.ibm.com/certify/exams/C1000-173

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IBM C1000-173 考試大綱：

主題	簡介
主題 1	Plan for a Cloud Pak for Data Implementation: This section of the exam measures the skills of an Implementation Consultant and covers determining which Cloud Pak for Data services to deploy based on organizational needs. It involves sizing the Kubernetes OpenShift cluster appropriately for workload demands and planning backup and restore strategies to ensure data protection. Planning for high availability and disaster recovery is essential to maintain uninterrupted service. Multi-tenancy requirements must be understood to support multiple user groups securely on shared infrastructure. Migration requirements need assessment to transition existing data and workloads smoothly.
主題 2	Architect with AI Series: This section measures the skills of an AI Solution Architect and includes designing architectures for solutions involving various IBM Watson AI services. Architecting with Watson Assistant involves creating conversational AI interfaces. Watson Discovery solutions focus on building cognitive search and content analytics applications. Watson Pipelines solutions involve orchestrating data science workflows. Watson OpenScale architectures enable AI model monitoring and governance. Architecting with Match 360 supports personalized engagement by integrating multi-channel customer insights.
主題 3	Architect with Analytic Services: This domain targets a Data Analytics Architect and focuses on designing solutions using analytic components of Cloud Pak for Data. Architecting with DataStage involves creating data integration and ETL pipelines. Data Refinery architectures prepare and cleanse data for analysis. Db2 Big SQL solutions address querying large distributed data sets with SQL, facilitating analytics across diverse data sources.
主題 4	Security Requirements: This domain targets a Security Architect and focuses on planning security for a Cloud Pak for Data deployment. It includes managing certificates that secure communications, identity management systems, and access and authorization controls to enforce secure and compliant user and service interactions. The auditing features and their integration with enterprise audit systems are crucial to ensure traceability and accountability. Asset interchange security involves safeguarding data movement between services.
主題 5	Architect with Data Governance Services: This section evaluates skills of a Data Governance Specialist, covering the architecture of knowledge catalogs to enable data discovery and management. Data Privacy architectures ensure compliance with regulatory requirements around data protection. Knowledge Accelerators involve designing solutions that speed up data governance processes through predefined policies and templates.

最新的 IBM Certified Architect C1000-173 免費考試真題 (Q57-Q62):

問題 #57
How are caches defined in IBM Data Virtualization?

A. They are created automatically based on usage patterns.
B. DataStage flows are created in a project for maintaining caches.
C. Caches are manually defined based on recommendations and monitoring data.
D. Caches are suggested based on statistics collected during data source configuration.

答案：C

解題說明：
In IBM Data Virtualization, caches must be manually defined by administrators. While monitoring and query performance statistics can guide where caching would be beneficial, the creation and configuration of caches (e.g., refresh schedules and scope) are manual tasks. There is no automated cache creation mechanism (A), nor are DataStage flows used for cache maintenance (B). Suggestions based on statistics (D) may assist administrators, but they do not automatically create the caches.

問題 #58
What is the purpose of the IBM Data Replication service?

A. To monitor database activity.
B. To integrate and synchronize data.
C. To provide a unified view of disparate data sources.
D. To transform and validate data moving from source to target.

答案：B

解題說明：
The IBM Data Replication service in Cloud Pak for Data is designed to integrate and synchronize data between various systems, ensuring that data in target systems is kept up-to-date with the source systems. It supports near real-time replication and change data capture (CDC) mechanisms, making it ideal for analytics environments that require continuous synchronization.
The service is not a tool for database activity monitoring (A), creating unified virtual views (B), or performing heavy data transformations (D).

問題 #59
Understanding instance limitations in Watson Assistant is critical for what reason?

A. To optimize budget allocation for cloud resources
B. To ensure compliance with data protection regulations
C. To prevent overutilization of computational resources
D. To maximize the performance of machine learning models

答案：A

問題 #60
What scenario best illustrates the effective use of Db2 Graph services?

A. For basic CRUD operations without relationships
B. Managing complex relationships and pattern recognition
C. Simple data aggregation without the need for graph theory
D. When handling flat, tabular data

答案：B

問題 #61
Which Db2 Big SQL component uses system resources efficiently to maximize throughput and minimize response time?

A. Hive
B. Scheduler
C. StreamThrough
D. Analyzer

答案：C

解題說明：
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.

問題 #62
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