IBM Cloud Pak for Data V4.x Data Engineer Intermediate Practice Exam: Medium Difficulty 2025

A data engineer needs to design a Cloud Pak for Data deployment that supports multiple analytics workloads with different resource requirements. The finance team needs guaranteed resources for month-end reporting, while the data science team requires flexible scaling. Which architectural approach best meets these requirements?

A data engineer is building a DataStage job that needs to load data from three different source systems into a data warehouse. Two sources are updated hourly, while one is updated daily. The job must ensure data consistency and handle scenarios where one source is temporarily unavailable. What is the most appropriate design pattern?

An organization has implemented Watson Knowledge Catalog for data governance. The compliance team requires that all datasets containing customer email addresses be automatically classified and have access restricted to authorized users only. What combination of features should the data engineer configure?

A data engineer needs to provide business analysts with access to data from five different database systems without physically moving the data. The analysts use various BI tools and need to join data across these sources. Query performance for frequently accessed data must be optimized. Which Data Virtualization approach should be implemented?

During a DataStage ETL job execution, the data engineer notices that a Transformer stage is causing a performance bottleneck when processing 50 million records. The transformation logic includes multiple conditional statements and lookups. What is the most effective optimization strategy?

A data governance initiative requires tracking data lineage from source systems through transformations to analytical reports. The organization uses DataStage for ETL and Watson Knowledge Catalog for governance. How should the data engineer ensure end-to-end lineage visibility?

An organization's Cloud Pak for Data platform hosts multiple services including DataStage, Data Virtualization, and Watson Studio. The platform administrator needs to ensure high availability and disaster recovery capabilities. Which architectural components must be configured?

A data engineer needs to create a virtualized view that joins customer data from an Oracle database with transaction data from a DB2 database. The Oracle database contains 10 million customer records, while DB2 has 500 million transactions. Analysts will filter by specific customer IDs. How should the virtual view be optimized?

A DataStage job needs to process incremental updates from a source table that tracks changes using a last_modified timestamp. The job runs every 4 hours and must process only records modified since the last successful run, even if previous runs failed. What implementation approach ensures data completeness?

An enterprise has published multiple data assets in Watson Knowledge Catalog with different sensitivity levels. The data engineer needs to implement a policy where data stewards must approve access requests for assets tagged as 'Confidential', while 'Public' assets are freely accessible. How should this be configured?