Answer: The queries attached to the dashboard might all be connected to their own, unstarted Databricks clusters.

We need to choose which option fails to explain the delay (i.e., which one is not a valid reason). Evaluate each: A. If the SQL endpoint (Databricks SQL warehouse) is stopped, starting it when a query runs can take a few minutes — valid cause. B. If queries are complex/scan large data, they can naturally take minutes — valid cause. C. Databricks SQL queries can have result caching or checks; but dashboard queries don't typically "check for new data" causing delay; however, more precisely the query may check metadata or refresh policies — this is less likely but could be considered valid depending on interpretation. But more likely they might be false — need to weigh. D. A job using a non-pooled endpoint may need to start a cluster which takes time — valid cause. E. Databricks SQL dashboards run on SQL endpoints (warehouses) not on separate customer-managed clusters for each query; queries do not connect to their own unstarted Databricks clusters. This is not an explanation for slow dashboard updates — therefore E fails to explain the delay. Therefore, the best answer is E. Explanation: Databricks SQL dashboards run queries on SQL endpoints (warehouses). Each query would not be using its own independent unstarted Databricks cluster — that scenario is unlikely. Option C is somewhat plausible but E is clearly incorrect.

Author: LeetQuiz .