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IBM C1000-173 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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 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 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 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.

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q79-Q84):

NEW QUESTION # 79
What is a Data Refinery flow in Cloud Pak for Data?

Answer: D

Explanation:
A Data Refinery flow in Cloud Pak for Data is an ordered set of data operations (transformations) that are applied to tabular data. It is used to cleanse, shape, and prepare data for analysis or machine learning. Users can apply filters, joins, aggregations, and custom expressions. It is not a storage location (A), ML model (B), or a visualization tool (D), though visual previews of transformed data are available.


NEW QUESTION # 80
When planning an environment for multiple Cloud Pak deployments, what is crucial?

Answer: D


NEW QUESTION # 81
Which IBM Cloud Pak for Data service would you use for building AI models and running experiments?

Answer: B


NEW QUESTION # 82
What is a key benefit of implementing a Public Key Infrastructure (PKI) in certificate management?

Answer: A


NEW QUESTION # 83
Which of the following are essential considerations when scaling Watson Assistant solutions across different geographies? (Select two)

Answer: B,C


NEW QUESTION # 84
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