IBM Cloud Pak for Data v4.x Solution Architect Intermediate Practice Exam: Medium Difficulty 2025

A financial services organization is planning to deploy Cloud Pak for Data across multiple geographies to support data residency requirements. They need to ensure consistent metadata management and data lineage tracking across all deployments while maintaining separate data stores in each region. Which architectural approach best addresses these requirements?

During a Cloud Pak for Data installation on OpenShift, the solution architect discovers that the Watson Studio service fails to provision with errors related to persistent volume claims. The OpenShift cluster has dynamic storage provisioning configured. What is the most likely cause and resolution?

A retail company wants to implement a data architecture where operational data from multiple database systems (Oracle, PostgreSQL, and Db2) can be accessed and joined without physical data movement. The business analysts need to create reports combining data from all three sources. Which Cloud Pak for Data capability should be the primary solution, and what is a key consideration?

An organization has successfully deployed Cloud Pak for Data and now needs to integrate it with their existing enterprise LDAP directory for user authentication and group-based access control. Multiple project teams with different data access requirements will use the platform. What is the recommended approach for implementing this integration?

A data governance team needs to ensure that sensitive customer data (PII) is properly classified, protected, and tracked across Cloud Pak for Data. They want to automatically discover sensitive data in new data sources and enforce access policies. Which combination of capabilities should be implemented?

A manufacturing company is deploying Cloud Pak for Data to support both data science teams and business analysts. The data science teams require GPU resources for deep learning model training, while analysts need standard compute for reporting. What architectural consideration is most important for resource optimization?

A data science team has developed a machine learning model in Watson Studio that performs customer churn prediction. They need to deploy this model for real-time scoring via REST API and monitor its performance for model drift. What is the complete deployment approach?

An enterprise is planning Cloud Pak for Data capacity for 200 concurrent users across data engineering, data science, and business analytics use cases. They need to determine compute and storage requirements. Which factors should be prioritized in the sizing estimation?

A healthcare organization needs to virtualize patient data from multiple hospital systems while ensuring that queries include only data the user is authorized to see based on their hospital affiliation and role. Some users should see masked data for certain fields. How should this be implemented using Cloud Pak for Data?

After deploying AutoAI models in production, a data scientist notices that model accuracy has degraded over time. The organization wants to implement an automated retraining pipeline. What approach should be implemented using Cloud Pak for Data capabilities?