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Real IBM C1000-173 Exam Questions [2025] - Secret To Pass Exam In First Attempt

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IBM C1000-173 Exam Syllabus Topics:

Topic
Details

Topic 1

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.

Topic 2

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.

Topic 3

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.

Topic 4

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.

Topic 5

Architect with Data Source Services: This domain measures expertise of a Data Integration Architect and includes architecting solutions with data replication technologies to synchronize data across systems. IBM Data Virtualization architecture enables access to and querying of disparate data sources without data movement. Architecting with watsonx.data focuses on building intelligent data lakes and query engines. Architecting with Db2-related services involves designing scalable data management and processing architectures using IBM's Db2 platforms.

IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q15-Q20):

NEW QUESTION # 15
What mechanism is essential for securing data during transit in asset interchange?

A. Data at rest encryption
B. Role-based access control
C. Data in transit encryption
D. Periodic data backups

Answer: C

NEW QUESTION # 16
What post-installation step is essential for enhancing Watson Assistant's performance? (Select two)

A. Training the AI model with domain-specific data
B. Increasing the physical memory of the server
C. Setting up feedback loops for continuous improvement
D. Increasing the physical memory of the server

Answer: A,C

NEW QUESTION # 17
Which Watson Pipeline component manages pipeline errors, typically used with DataStage?

A. Fault Settings
B. Default Control
C. Error Handling
D. Process Termination Window

Answer: C

Explanation:
In Watson Pipelines within IBM Cloud Pak for Data, error management is handled by the Error Handling component. This feature allows developers and pipeline administrators to define how pipeline failures are processed-whether to stop execution, continue, or trigger alternate flows. It ensures controlled behavior in response to job failures, particularly in complex ETL pipelines like those built with DataStage. Error Handling is a configurable element of pipeline orchestration and is typically used to enhance fault tolerance and control error propagation in production workflows.

NEW QUESTION # 18
In the context of auditing, what does immutable logging ensure?

A. Log storage optimization
B. User authentication
C. High availability
D. Non-repudiation

Answer: D

NEW QUESTION # 19
Comparing data replication with an ETL tool, which feature is exclusive to data replication concerning real-time data changes?

A. Immediate data synchronization
B. Deferred data update capabilities
C. Batch processing of data changes
D. Reduced data consistency

Answer: A

NEW QUESTION # 20
......

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