Q:

Your company has been experiencing performance issues with their Tier-1 environment during data migration processes, which involve large datasets.

You need to optimize the data migration process to handle large volumes of data more efficiently and reduce the overall migration time.

What should you do? Each correct answer presents a complete solution. Choose three.

 

Wrong: Increase the number of batch threads beyond 16 without conducting full performance testing.

Wrong: Use OData for importing and exporting large datasets.

Wrong: Implement continuous number sequences with preallocation for all data entities.

Turning off change tracking helps improve performance during data migrations as it is not needed for full data imports and slows down the process. Enabling set-based processing allows for bulk operations instead of single record operations, which is more efficient for large datasets. Creating a data migration batch group ensures that migration jobs run during periods of low system activity, reducing the risk of performance bottlenecks. Increasing the number of batch threads beyond 16 without performance testing may negatively impact system performance and is not recommended. Using OData for large dataset migration is not advised due to its limitations in handling large volumes. Continuous number sequences with preallocation can cause locking issues and are not related to data migration performance.

Query optimization principles - Training | Microsoft Learn

Product-specific guidance for optimizing performance - Dynamics 365 | Microsoft Learn