IBM C1000-173 Exam Vce Format - Cert C1000-173 Guide

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IBM C1000-173 Exam Syllabus Topics:

TopicDetails
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
  • 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 3
  • 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.
Topic 4
  • 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.

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IBM C1000-173 Practice Test [2026]

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q24-Q29):

NEW QUESTION # 24
An architect is working with a team to configure Dynamic Workload Management for a single DataStage instance on Cloud Pak for Data. Auto-scaling has been disabled and the maximum concurrent jobs has been set to 5. What will happen if a sixth concurrent job is executed?

Answer: B

Explanation:
Queueing mechanism is in place. Since the maximum concurrent jobs are limited to 5, the sixth job will not start immediately. Instead, it will queue and wait for one of the currently running jobs to complete, making room for the sixth job to execute.


NEW QUESTION # 25
What mechanism is essential for securing data during transit in asset interchange?

Answer: A


NEW QUESTION # 26
What must be created to enable the Cloud Pak for Data platform to use a company's custom CA certificate to validate certificates from internal servers?

Answer: B

Explanation:
To enable IBM Cloud Pak for Data to trust certificates from internal servers using a custom Certificate Authority (CA), the correct method is to create a Kubernetes ConfigMap that contains the CA certificate. This ConfigMap is referenced by the platform's foundational services to include the CA in the trusted root store.
Secrets are typically used for storing sensitive data like private keys and TLS certificates but are not used for adding trusted root CAs at the platform level. A ConfigMap is explicitly required by the platform to inject the CA trust into the certificate validation chain.


NEW QUESTION # 27
What is the primary purpose of IBM Cloud Pak for Data?

Answer: D

Explanation:
IBM Cloud Pak for Data is an integrated data and AI platform that enables businesses to modernize their data architecture. It provides a complete solution for data management, analytics, AI, and data governance, helping organizations make data-driven decisions.


NEW QUESTION # 28
Which data processing engine is used for Data Privacy Masking flows?

Answer: A

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 # 29
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