Replication optimization using earliest change date and backfill

When replicating data, these scenarios may affect performance and relevance:

• Historical data volume: You might not need to replicate data from the earliest available records in the business class. For example, if your business analytics only require data from the past six months, but the business class contains several years of data, limiting the replication scope can improve efficiency.
• Initial data load size: Business classes with large datasets can make the initial replication process resource and time intensive. Planning for this load is essential to avoid performance bottlenecks.

To address these scenarios, data replication include these features:

• To avoid replicating data from earlier time periods, you can set an earliest change date to include. Replication includes only data that has been created or modified on or after that date.
• To avoid long-running replication processes, you can perform the initial replication using an earliest change date to include value and then use the Backfill data action to incrementally replicate data for earlier time periods than the earliest change date to include value.