I'm unhappy with our warehouse because dashboards slow down when more users log in; what fixes that?

If dashboards get slow when more users log in, the usual fixes are to improve concurrency, query performance, and resource isolation in your warehouse.

Most common fixes

• Use a larger warehouse / cluster
  More CPU, memory, and I/O helps if the bottleneck is compute or contention.

• Enable or increase multi-cluster scaling
  This lets the warehouse spin up additional clusters when many users run queries at once, reducing queueing.

• Add result caching / query caching
  If the same dashboards are queried repeatedly, cached results can make logins and refreshes much faster.

• Optimize the dashboard queries

  • Reduce joins and nested subqueries
  • Pre-aggregate where possible
  • Filter earlier
  • Avoid selecting unnecessary columns

• Use materialized views or summary tables Great for BI dashboards that repeatedly read the same metrics.

• Separate workloads Put dashboard/BI traffic on its own warehouse, separate from ETL or ad hoc analyst queries.

• Tune concurrency settings / queues If queries are waiting, the issue may be too many simultaneous requests for the current warehouse size.

• Check for lock/contention or long-running queries Sometimes one heavy query is starving many small dashboard queries.

Quick rule of thumb

• If users are waiting in queue → add multi-cluster or scale up.
• If queries are running slowly → optimize SQL / add materialized views / increase warehouse size.
• If the problem happens only during ETL runs → isolate dashboard workloads.

If you tell me which warehouse you’re using (Snowflake, Redshift, BigQuery, Databricks SQL, etc.), I can suggest the exact setting or feature to change.