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NEW QUESTION # 122
In a ZDM scenario with a large database and high transaction volume, which of the following techniques can help mitigate potential performance issues during cutover?
Answer: D
Explanation:
Here's a breakdown of why:
Staged cutover minimizes the impact on the source database during the migration process by gradually transitioning objects or partitions to the target database. This helps to avoid overwhelming the source database with a sudden influx of traffic.
Reduced risk: A staged cutover approach allows you to identify and address any issues with individual components before proceeding with the entire migration, reducing the risk of a complete failure.
Improved performance: By gradually transferring objects or partitions, you can more effectively manage the workload on both the source and target databases, leading to better overall performance.
The other options are not as effective in mitigating performance issues during cutover:
a). Enabling archive logging: While archive logging can be useful for disaster recovery, it's not directly related to improving performance during cutover.
b). Performing a full database export and import: This approach can be time-consuming and may not be suitable for large databases with high transaction volumes.
c). Utilizing supplemental logging: Supplemental logging can be helpful for troubleshooting, but it's not a direct solution for mitigating performance issues during cutover.
NEW QUESTION # 123
Which of the following considerations should be prioritized to ensure a successful migration and avoid post-migration data inconsistencies?
Answer: C
Explanation:
Performing a full database validation post-migration to identify any inconsistencies is the most crucial consideration to ensure a successful migration and avoid post-migration data inconsistencies.
Here's why:
Comprehensive Check: A full database validation verifies the integrity of data, relationships, and constraints after the migration.
Error Detection: It helps identify any discrepancies, missing data, or incorrect values that may have occurred during the migration process.
Data Quality: Ensuring data consistency is essential for maintaining data integrity and preventing errors in downstream applications.
While the other options are also important, they are not as directly related to preventing post-migration data inconsistencies:
a) Optimizing network bandwidth for faster data transfer: Faster data transfer can improve the overall migration speed but doesn't guarantee data consistency.
b) Maintaining the order of table creation during the migration process: While this can be important for certain scenarios, it's not directly related to preventing data inconsistencies.
c) Disabling referential integrity constraints before migration and re-enabling them afterward: This is a common practice to improve migration speed, but it doesn't guarantee data consistency. It's essential to validate data after re-enabling constraints.
NEW QUESTION # 124
During the Unplug/Plug migration process, what happens after the read-only snapshot (PDB) is created within the MTCD?
Answer: A
Explanation:
Here's a breakdown of why:
Unplug/Plug is a method for migrating a database to the Multitenant Container Database (MTCD) without disrupting operations.
The initial step involves creating a read-only snapshot (PDB) of the source database.
After the snapshot is created, the source database continues to operate as normal. This ensures minimal downtime and avoids affecting users.
To keep the PDB in sync with the source database, periodic refreshes are performed. These refreshes update the PDB with the latest changes from the source.
NEW QUESTION # 125
In the context of Data Pump import with potential data inconsistencies, which of the following options provides the most robust error handling mechanism?
Answer: D
Explanation:
Here's a breakdown of why:
User-defined error handling: This approach provides the most flexibility and control over how data quality issues are handled during the import process. You can define custom routines to log errors, reject invalid data, or take other actions based on specific error conditions.
The other options are less robust:
A). Disabling constraints can lead to data integrity issues if not handled carefully. It's not a reliable error handling mechanism.
B). The IGNORE parameter can be useful for skipping rows with errors, but it may not be suitable for all scenarios, as it can lead to data loss.
C). The RESUMABLE parameter allows you to resume the import process after encountering errors, but it doesn't address the root cause of the data quality issues.
NEW QUESTION # 126
Which of the following is NOT a typical consideration when analyzing migration strategies?
Answer: B
Explanation:
While backups are important for safety, the number of available backup copies is not a typical consideration when analyzing migration strategies.
NEW QUESTION # 127
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