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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
Related Certifications:IBM Cloud Pak for Data Data Engineer
IBM Cloud Pak for Data Administrator
Available Languages:English
Exam Duration:90 minutes
Exam Price:USD 200 (varies by region)
Certificate Validity Period:3 years
Exam Format:Multiple response, Multiple choice
Real Exam Qty:60-70
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:

TopicDetails
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
  • 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 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.
Topic 4
  • 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 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.

IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q129-Q134):

NEW QUESTION # 129
Which Cloud Pak for Data service is used to cleanse and shape tabular data?

Answer: D

Explanation:
Data Refinery is the dedicated data preparation service in IBM Cloud Pak for Data. It enables users to cleanse, shape, filter, and enrich tabular datasets through a graphical interface. Users can create data preparation flows that integrate seamlessly with Watson Studio and other services. Data Manager and Data Wrangler are not services available in CP4D, and Watson Data is not a recognized component. Data Refinery is the officially supported tool for this purpose.


NEW QUESTION # 130
Are there any special considerations for the client to migrate existing server jobs to DataStage in Cloud Pak for Data?

Answer: B

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 # 131
For ensuring high availability and disaster recovery in Cloud Pak for Data, which of the following components should be made redundant?

Answer: B,C,D


NEW QUESTION # 132
What is used to monitor workloads when running Db2 Warehouse as a Cloud Pak for Data service?

Answer: B


NEW QUESTION # 133
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 # 134
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