Free IBM Cloud Pak for Data v4.x Data EngineerPractice Test

An organization is deploying IBM Cloud Pak for Data and needs to understand the infrastructure requirements. Which component serves as the foundational platform for Cloud Pak for Data deployment?

A data engineer needs to configure DataStage for ETL operations in Cloud Pak for Data. Which service must be provisioned first before DataStage can be deployed?

Your organization has deployed Cloud Pak for Data across multiple namespaces in OpenShift. A data engineer reports that users in one namespace cannot access assets shared from another namespace. What is the MOST likely cause of this issue?

Which deployment topology should be recommended for a production environment requiring high availability and disaster recovery capabilities in Cloud Pak for Data?

A company wants to separate development, testing, and production workloads in their Cloud Pak for Data environment. What is the recommended approach?

A data engineer needs to integrate data from an on-premises Oracle database with cloud-based data sources. Which Cloud Pak for Data service provides the capability to query data across these heterogeneous sources without moving the data?

When designing a DataStage job for incremental data loading, which approach is considered best practice for tracking changes in source systems?

A DataStage job is failing with 'insufficient memory' errors during a large-scale transformation. The job processes 10 million records with complex joins. What is the MOST effective optimization strategy?

When configuring Data Virtualization in Cloud Pak for Data, a data engineer needs to expose virtualized data to business analysts through a standardized interface. Which feature should be used?

A data pipeline requires real-time data integration from multiple streaming sources including Kafka and Event Streams. Which capability in Cloud Pak for Data should be leveraged?

When connecting Data Virtualization to a remote data source, what authentication method provides the most secure and scalable approach for enterprise deployments?

A complex DataStage job needs to process data from five different source systems, apply business rules, and load into three target systems. What design pattern best supports maintainability and reusability?

What is the primary purpose of Watson Knowledge Catalog in the Cloud Pak for Data ecosystem?

A data engineer needs to ensure that sensitive customer data in the catalog is automatically identified and classified. Which Watson Knowledge Catalog feature should be configured?

An organization needs to implement data masking for production data used in development environments. Where should data protection rules be configured in Cloud Pak for Data?

A business glossary term needs to be associated with multiple data assets across different data sources. What is the correct approach in Watson Knowledge Catalog?

A data governance team needs to track which reports and dashboards are impacted when a source table schema changes. Which capability provides this visibility?

When implementing a data governance workflow, certain data assets should only be accessible after approval from a data steward. How should this be configured in Cloud Pak for Data?

A DataStage job is running slower than expected. Analysis shows that the job is spending most of its time waiting for I/O operations. What should be investigated first?

Multiple Data Virtualization queries are timing out when accessing a specific remote data source. The source database administrators report no performance issues on their end. What is the MOST likely cause and solution?

To optimize the performance of a heavily-used DataStage job that processes data nightly, which metric should be monitored to identify if parallel processing is being effectively utilized?

After upgrading Cloud Pak for Data, users report that previously functional Watson Knowledge Catalog connections to a legacy data source are failing. What troubleshooting step should be performed first?