What should an Architect suggest to avoid data duplication after loading a large contact dataset into Salesforce?

The most effective approach to avoid data duplication after loading a large contact dataset into Salesforce is to utilize an off-platform de-duplication tool before loading. This strategy helps ensure that the dataset is cleansed and validated before it enters the Salesforce environment. Such tools can scan the dataset for duplicates based on customizable criteria and may provide advanced matching algorithms to identify potential duplicates that may not be apparent through standard methods.

Addressing duplicates at this stage minimizes issues within Salesforce, as the cleaned data will contribute to maintaining data integrity and optimizing performance. Moreover, it alleviates the need for post-load management, which can be resource-intensive and can delay the usability of the data within Salesforce.

While the other choices also address duplication, they generally involve handling data after it has already been loaded into Salesforce. This can complicate the data management process, potentially lead to performance issues, and require additional resources for remediation. Thus, preventing duplication before loading is the most proactive and efficient method.