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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	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	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 4	Security Requirements: This domain targets a Security Architect and focuses on planning security for a Cloud Pak for Data deployment. It includes managing certificates that secure communications, identity management systems, and access and authorization controls to enforce secure and compliant user and service interactions. The auditing features and their integration with enterprise audit systems are crucial to ensure traceability and accountability. Asset interchange security involves safeguarding data movement between services.
Topic 5	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.

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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q180-Q185):

NEW QUESTION # 180
When creating a Db2 Big SQL service instance, which two service resource items should be taken into account when sizing the cluster?

A. Amount of memory
B. Maximum expected throughput
C. Number of virtual cores
D. Number of physical cores
E. Number of workers

Answer: A,E

Explanation:
When provisioning a Db2 Big SQL service instance in IBM Cloud Pak for Data, key considerations include the amount of memory available per worker node and the total number of worker nodes. These factors directly affect query execution parallelism and system capacity. The system does not distinguish between physical and virtual cores at the configuration level. Throughput is an outcome of sizing, not a direct sizing parameter.
Therefore, memory and number of workers are the two most critical sizing metrics.

NEW QUESTION # 181
Why would an organization implement the data privacy capabilities of Cloud Pak for Data?

A. It restricts access to sensitive data.
B. It provides trusted, consistent data.
C. It hides owner information for specific datasets.
D. It prevents unauthorized access to the platform.

Answer: A

Explanation:
The primary goal of the data privacy capabilities in IBM Cloud Pak for Data is to restrict access to sensitive data such as personally identifiable information (PII), financial records, or protected health information. This is achieved using Data Protection Rules, dynamic masking, and policy enforcement across services like IBM Knowledge Catalog and Data Virtualization. It ensures compliance with data governance policies and external regulations. While trusted data and platform security are important, those are addressed by other services and features.

NEW QUESTION # 182
What is the purpose of configuring access to a Git repository associated with a project in Cloud Pak for Data?

A. To collaborate with others, manage file versions, and enable branching.
B. To delete the repository and create a new one.
C. To enhance data visualization in JupyterLab or RStudio.
D. To manage the deployment of a model to a project space.

Answer: A

Explanation:
Configuring access to a Git repository in Cloud Pak for Data projects allows teams to collaborate on code, notebooks, and assets while benefiting from version control and branching. This setup ensures that all project files can be tracked, reverted, or merged, enabling collaborative development and continuous integration workflows. It is not used for model deployment management (B) or visualization enhancements (C). Option D is unrelated to the actual purpose of Git integration.

NEW QUESTION # 183
What is the primary goal of High Availability in computing environments?

A. To ensure a system operates at its peak capacity
B. To maximize system downtime
C. To reduce the efficiency of backup processes
D. To minimize downtime and prevent data loss

Answer: D

NEW QUESTION # 184
The data integration team at a financial services company has always struggled to manage resources as the number of integration jobs changes throughout the month.
Which two settings are available when configuring Dynamic Workload Management for a specific DataStage instance?

A. Job Log Retention (log_retention)
B. ETL/ELT Mode (ETL, ELT, or Hybrid)
C. Job Count (JobCount)
D. Auto-scaling (computePodsMin, computePodsMax)
E. Job Configuration File (APT_CONFIG_FILE)

Answer: C,D

NEW QUESTION # 185
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