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

A financial services company is designing a Cloud Pak for Data architecture to support multiple business units with varying data governance requirements. The compliance team requires strict data isolation between departments, while the analytics team needs shared access to anonymized datasets. What architectural approach best addresses these requirements?

During a Cloud Pak for Data installation on Red Hat OpenShift, the solution architect needs to ensure high availability for critical Watson services. The customer has a three-node OpenShift cluster. Which configuration approach should be recommended?

A retail organization needs to implement data quality monitoring for their customer database in Cloud Pak for Data. They want to automatically profile data, identify quality issues, and track improvements over time. Which combination of services should the solution architect recommend?

An enterprise is deploying Watson Machine Learning on Cloud Pak for Data to serve real-time predictions for a fraud detection application. The model must respond within 100ms and handle 1000 requests per second during peak hours. What deployment configuration should be prioritized?

A solution architect is designing the network architecture for Cloud Pak for Data that will integrate with multiple on-premises data sources behind corporate firewalls. The security team requires encrypted communication and minimal firewall rule changes. What connectivity approach should be recommended?

After installing Cloud Pak for Data, the administrator notices that some services are in a pending state due to insufficient storage. The environment uses dynamic provisioning with a default storage class. What should be the first troubleshooting step?

A healthcare organization needs to implement data lineage tracking for regulatory compliance. They use DataStage for ETL, Data Virtualization for data access, and Watson Knowledge Catalog for governance. How should end-to-end lineage be achieved?

A data science team is building multiple machine learning models in Watson Studio that share common data preprocessing steps. The team wants to ensure consistency and reduce redundant work. What approach should the solution architect recommend?

An organization is architecting a Cloud Pak for Data solution that must support both structured data analytics and unstructured document analysis. The solution needs to scale independently for each workload type. What architectural pattern is most appropriate?

A company has deployed Watson OpenScale to monitor ML models in production. They notice that model accuracy has degraded over time. Which combination of Watson OpenScale capabilities should be used to identify and address this issue?