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IBM C1000-173 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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.

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q107-Q112):

NEW QUESTION # 107
Are there any special considerations for the client to migrate existing server jobs to DataStage in Cloud Pak for Data?

Answer: D

Explanation:
Legacy DataStage server jobs are not automatically compatible with DataStage on Cloud Pak for Data, which uses a parallel engine architecture. MettleCI is the recommended tool to convert server jobs into parallel jobs before migration. This conversion allows reusability and ensures the migrated jobs can run efficiently in the CP4D environment. Direct migration without modification (option D) is not possible, and they do not migrate to Watson Pipelines (option A).


NEW QUESTION # 108
Which of the following are considered when determining the correct storage options for IBM Cloud Pak for Data?

Answer: C


NEW QUESTION # 109
Which of the following strategies are crucial for planning an effective backup and restore process in a Cloud Pak for Data environment?

Answer: C,D


NEW QUESTION # 110
Which two Cloud Pak for Data services support the multi-tenancy mechanism of installing the service once and provisioning the workloads in tethered projects?

Answer: B,C

Explanation:
Cloud Pak for Data supports service-level multi-tenancy by enabling some services to be installed centrally and then provisioned into user "tethered" namespaces (projects). In version 4.7, Analytics Engine (Apache Spark) and IBM Data Virtualization services support this tethered#project model: they can be installed once and then instantiated per project across multiple tenants. Core services like Db2, Cognos Analytics, and Watson Pipelines in 4.7 require installation per instance and do not yet support tethered#namespace provisioning via multi#tenant model.


NEW QUESTION # 111
Which data processing engine is used for Data Privacy Masking flows?

Answer: C

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 # 112
......

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