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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
Exam Price:	USD 200 (varies by region)
Exam Format:	Multiple response, Multiple choice
Exam Duration:	90 minutes
Certificate Validity Period:	3 years
Real Exam Qty:	60-70
Related Certifications:	IBM Cloud Pak for Data Data Engineer IBM Cloud Pak for Data Administrator
Available Languages:	English
Recommended Training:	IBM Cloud Pak for Data Learning Resources
Exam Registration:	IBM Certification Portal
Sample Questions:	IBM C1000-173 Sample Questions
Exam Way:	Online proctored exam (remote) or authorized testing center
Pre Condition:	No strict mandatory prerequisites, but strong familiarity with IBM Cloud Pak for Data architecture and services is recommended.
Official Syllabus URL:	https://www.ibm.com/training/certification

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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	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 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	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.

IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q85-Q90):

NEW QUESTION # 85
When upgrading to Cloud Pak for Data v4.7, why must an export/import of governance data be performed?

A. The underlying Db2 repository has been altered.
B. Containers are ephemeral and cannot persist the data.
C. Components of Information Server have been removed from the product.
D. Catalog data must be relocated to persistent storage.

Answer: A

Explanation:
During the upgrade to Cloud Pak for Data version 4.7, significant changes were made to the underlying metadata repository, which is powered by Db2. These changes affect how governance data is stored and accessed, and an export/import is necessary to ensure compatibility and data integrity. The export step extracts governance metadata using the supported utility, and after the upgrade, it is re-imported into the upgraded structure. This is not due to container ephemerality or storage changes, but because of schema and format changes in Db2.

NEW QUESTION # 86
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. Cloud Pak for Data operators cannot be co-located with the IBM Cloud Pak foundational services operators.
B. Partial installation of the Cloud Pak for Data has to be done manually for the first time installation.
C. Automatic installation cannot be done for any of the Cloud Pak for Data services.
D. Cloud Pak for Data cannot be installed on an existing cluster.

Answer: B

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 # 87
For achieving optimal performance in IBM Cloud Pak for Data, which storage solution should be utilized for analytical workloads requiring high IOPS?

A. File storage
B. Block storage
C. SSD-based storage
D. Object storage

Answer: C

NEW QUESTION # 88
Which two features are valid only when deploying Cloud Pak for Data on-premises?

A. Services are automatically updated.
B. Network security is managed by IBM.
C. Persistent storage is always used.
D. The number of OpenShift nodes is configured by the administrator.
E. Compute resources are automatically scaled.

Answer: C,D

Explanation:
In on-premises deployments of IBM Cloud Pak for Data:
Administrators have full control over the number of OpenShift nodes, unlike cloud-managed environments where node scaling may be automatic or abstracted.
Persistent storage is always required and configured by the infrastructure team to meet service requirements and ensure data availability.
Auto-scaling of compute and automatic updates of services are not handled by IBM in on-prem setups.
Network security responsibilities also lie with the deploying organization, not IBM, in an on-premises model.

NEW QUESTION # 89
Which Db2 Big SQL component uses system resources efficiently to maximize throughput and minimize response time?

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

Answer: C

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 # 90
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