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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
Exam Format:Multiple choice, Scenario-based questions
Passing Score:66%
Exam Duration:90 minutes
Real Exam Qty:62
Available Languages:English
Certificate Validity Period:No fixed expiration
Related Certifications:IBM Certified Specialist - Cloud Pak for Data
IBM Certified Solution Advisor - Cloud Pak for Data
Recommended Training:IBM Cloud Pak for Data Architecture and Implementation
Solution Architect: IBM Cloud Pak for Data v4.x
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 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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.

IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q167-Q172):

NEW QUESTION # 167
Which two of the following can be used with Watson Pipelines?

Answer: C,D

Explanation:
Watson Pipelines in Cloud Pak for Data support orchestration of diverse workload types including notebooks (Python or similar interactive environments) and scripts such as Bash. These pipeline components allow integration of notebook cells or shell scripts as tasks. There is no built#in support for executing PowerShell tasks directly (unless wrapped in Bash-like containers), and Postgres is used as a data source-not a pipeline component type. While Db2 Big SQL can be invoked within a notebook or script, it is not itself a pipeline component. Therefore the supported types in pipelines are notebooks and Bash scripts.


NEW QUESTION # 168
Which architectural consideration is crucial when deploying IBM Cloud Pak for Data on Red Hat OpenShift to ensure high availability?

Answer: C


NEW QUESTION # 169
Which API allows the management of users, roles, and authentication, as well as monitors the status of the Cloud Pak for Data platform?

Answer: C


NEW QUESTION # 170
What is a significant advantage of using Db2 services in a cloud environment?

Answer: B


NEW QUESTION # 171
Which type of search allows Watson Discovery to find the most relevant material in documents?

Answer: A

Explanation:
Watson Discovery employs advanced natural language processing and ranking algorithms that begin with keyword-based search. This type of search enables the tool to locate and return the most relevant document passages based on the presence and context of keywords in user queries. While it may also use metadata filters (facets), the core retrieval method remains keyword-driven to find relevance at both document and passage levels.


NEW QUESTION # 172
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