IBM Assessment: High Volume Data Migration v4 Advanced Practice Exam: Hard Questions 2025

A bank plans to migrate 180 TB from an on-prem RDBMS to Db2 on Cloud within a fixed weekend cutover window. The source system cannot tolerate long-running read locks and the target must be transactionally consistent at cutover. Network bandwidth is limited and variable. Which migration approach best balances minimal source impact, consistency, and cutover risk?

During assessment, you discover several terabyte-scale tables with heavy update activity and non-monotonic primary keys. The business requires the ability to validate row-level completeness post-migration without comparing full datasets (too expensive). Which validation strategy is most appropriate and scalable?

A migration involves regulated PII. Data must be masked in non-production targets while preserving referential integrity and enabling realistic performance testing. The same customer identifier appears across 30 tables, sometimes as a natural key string and sometimes embedded in JSON payloads. What is the best design to meet masking and integrity requirements at scale?

You are selecting IBM migration technology for a mixed workload: (1) several very large tables requiring high-throughput initial load, (2) near-zero-downtime cutover, (3) heterogeneous source/target platforms. Which pairing is the most appropriate architecture pattern?

In an IBM CDC deployment, replication latency suddenly increases from seconds to hours. Source CPU is stable, but the target shows frequent log flush waits and the CDC apply thread is active. Network is not saturated. What is the most likely bottleneck and the best next action?

A team uses parallel bulk loads into the target to meet a tight window. After load, they enable constraints and discover intermittent referential integrity violations even though the source was consistent. Investigation shows some child tables were loaded before parent tables due to dynamic scheduling. What is the best corrective strategy that preserves throughput and integrity for future runs?

A migration requires transforming legacy CHAR fields with mixed encodings into UTF-8, while preserving byte-level uniqueness semantics used by downstream systems. After migration, some distinct source values collapse to the same normalized Unicode string, breaking uniqueness constraints. What is the most appropriate mitigation?

You must choose between two architectures for high-volume migration to cloud: (1) direct transfer over VPN with compression, or (2) staging data in object storage near the target and loading from there. The network is unpredictable and the source can only export in large sequential reads at off-peak times. Which factor most strongly favors the object-storage staging approach?

After a bulk load, the target database exhibits poor query performance despite correct indexing definitions. EXPLAIN shows table scans and outdated cardinality estimates. Loads were performed with minimal logging and deferred index maintenance. What is the most effective remediation sequence to restore optimizer accuracy with minimal additional downtime?

During parallel load into the target, throughput plateaus and then decreases as more loader threads are added. Monitoring shows high disk queue depth, increased latch contention, and frequent page splits on several large indexes. What is the best tuning action to improve sustained load throughput?