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[General] 2026 C1000-173–100% Free New Test Voucher | High Pass-Rate New C1000-173 Test Di

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【General】 2026 C1000-173–100% Free New Test Voucher | High Pass-Rate New C1000-173 Test Di

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IBM C1000-173 Exam Syllabus Topics:
TopicDetails
Topic 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.
Topic 2
  • 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 3
  • 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 4
  • 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 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.

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q83-Q88):NEW QUESTION # 83
After installing Watson Assistant, which of the following tasks are crucial? (Select two)
  • A. After installing Watson Assistant, which of the following tasks are crucial?
  • B. Setting up a blockchain network
  • C. Integrating with existing databases and applications
  • D. Establishing a continuous integration pipeline
Answer: A,C

NEW QUESTION # 84
When planning for the data management console in Db2, what functionality is crucial for effective database management?
  • A. Limited visibility over data and queries
  • B. Avoiding integration with other Db2 services
  • C. Comprehensive monitoring and management features
  • D. Restricting user access to essential functionalities only
Answer: C

NEW QUESTION # 85
How does watsonx.data provide data sharing between Db2 Warehouse, Netezza, and any other data management solution?
  • A. Secure File Transfer Protocol (SFTP)
  • B. Iceberg tables
  • C. JSON file format
  • D. watsonx.data proprietary fast loader
Answer: B
Explanation:
watsonx.data uses Apache Iceberg tables as the open table format for data sharing across platforms like Db2 Warehouse, Netezza, and other compatible data management solutions. Iceberg provides a transactional and schema-evolution-friendly table layer, allowing multiple engines to read and write data concurrently. This approach avoids proprietary loaders or simple file transfers and ensures efficient interoperability between different systems.

NEW QUESTION # 86
Which of the following are essential considerations when scaling Watson Assistant solutions across different geographies? (Select two)
  • A. Consistent branding across regions
  • B. Localization of user interactions
  • C. Uniform data processing speeds
  • D. Region-specific legal compliance
Answer: B,D

NEW QUESTION # 87
An enterprise architect in a financial institute is deciding on the deployment option for Cloud Pak for Data on their existing OpenShift Container Platform cluster.
They have decided to use an automated deployment option and install Cloud Pak for Data from the cloud provider's marketplace. What are the limitations they may face with this decision?
  • A. Automatic installation cannot be done for any of the Cloud Pak for Data services.
  • B. Cloud Pak for Data cannot be installed on an existing cluster.
  • C. Partial installation of the Cloud Pak for Data has to be done manually for the first time installation.
  • D. Cloud Pak for Data operators cannot be co-located with the IBM Cloud Pak foundational services operators.
Answer: C
Explanation:
According to theIBM Cloud Pak for Data 4.7 Installation Guideand official IBM documentation, when deploying Cloud Pak for Data (CP4D) via a cloud provider marketplace (such as Red Hat OpenShift OperatorHub or a cloud marketplace), the deployment process offers an automated installation method that simplifies the setup. However, there are certain limitations and manual steps that may be required during the initial installation phase.
* CP4D supports installation on an existing OpenShift Container Platform cluster, so option A is incorrect.
* Some core services and operators, including foundational services, can be installed automatically via operators, so option B is incorrect.
* Cloud Pak for Data operators and IBM foundational services operators can coexist in the same OpenShift cluster, so option C is incorrect.
* Theofficial installation documentation for version 4.7specifies that the initial installation requires manual intervention for partial installation - for example, manually setting up foundational services or configuring specific operators before automated installation of the rest of the platform can continue smoothly. This partial manual setup is especially relevant when using marketplace deployment to ensure all prerequisites and configurations are met.
Exact extract from IBM Cloud Pak for Data 4.7 Installation documentation:
"When deploying Cloud Pak for Data via the OperatorHub or cloud marketplace, the initial setup requires manual installation of foundational services operators and configuration of the cluster environment before proceeding with the automated installation of Cloud Pak for Data services. Thispartial manual step ensures proper configuration and avoids conflicts during automated deployment."
-IBM Cloud Pak for Data Installation Guide v4.7, section "Installing from OperatorHub and Marketplace" References:
IBM Cloud Pak for Data 4.7 Installation Guide (https://www.ibm.com/docs/en/cloud-paks/cp-data/4.7?
topic=deployment-installing-from-operatorhub-marketplace)
IBM Knowledge Center for Cloud Pak for Data 4.7

NEW QUESTION # 88
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