Implementing a staging area to break down the data into smaller chunks (C) is the most effective and cost-efficient solution. It directly addresses the performance bottleneck by enabling parallel processing and reducing the load on the system, aligning with the organization's priorities of cost-effectiveness and scalability. Scaling up the dataflow cluster (A) may improve performance but at a higher operational cost, which contradicts the organization's emphasis on cost-effectiveness. Adding more indexes to the source database (B) might improve query performance but does not necessarily resolve the data loading bottleneck. Migrating to a premium data source (D) could offer better performance but at a significant cost, making it less aligned with the organization's priorities.