Data synchronisation for Cloud will be a standard because of residing data in different platform. The ideal synchronisation timing is always real time. Unfortunately, this can be costly and unrealistic. This is because data changes only happens for a particular moment. Thus, a full synchronisation is not efficient. How should we design for real time synchronisation?
User Behavioural Pattern
All data went through a lifecycle process from creation to modification and/or view only. A way to synch your data is to understand user behavioural pattern. This helps you to add in your trigger when there are user actions. The trigger to synch is usually to maintain modification consistency across the source and target system. It is also wise to close off the data and move these data as read only. That way, costly modification will not be needed for these data.
The most common synchronisation is schedule job. This method is brute force approach and helps ensure data integrity. However, it can be costly if data grows exponentially. It is usually cost effective to synch for changes instead of a full data synchronisation. A targeted schedule synchronisation is the most effective.
User behavioural patterns help to determine the data synchronisation you required in Cloud. A full synchronisation is costly and you should add filter to synchronise efficiency.