In a workspace with many data streams, what is the biggest downside of using calculated dimensions?

Using calculated dimensions in a workspace with many data streams primarily impacts performance. Calculated dimensions require additional processing power because they involve real-time computation based on the underlying dataset. As data streams increase in volume and complexity, the performance can degrade due to the additional load placed on processing resources. This can lead to slower query responses and prolonged processing times, especially when multiple users are accessing or calculating dimensions simultaneously.

While scalability and ease of maintenance are relevant considerations, they do not directly address the immediate impact on performance that arises from the computational demands of calculated dimensions. In high-traffic environments or those with large data volume, the strain that calculated dimensions put on the system can become a significant barrier to efficient data processing. Therefore, focusing on performance accurately captures the core downside of calculated dimensions in this context.