Databricks Certified Data Engineer - Associate

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.