Dashboard Performance Optimization AI Prompt

Diagnose and fix slow dashboard performance.

Dashboard tool: {{tool}}
Current load time: {{load_time}}
Data size: {{data_size}}
User complaint: {{complaint}}

1. Diagnose the bottleneck:

   Data query bottleneck:
   - Is the slow part the query or the rendering?
   - Enable query profiling in the tool — how long does each query take?
   - Are queries running on a large uncached dataset?
   - Are there multiple queries running sequentially that could run in parallel?

   Rendering bottleneck:
   - Too many data points in a single chart (scatter plot with 1M points)
   - Too many charts on a single page requesting data simultaneously
   - Heavy chart types (maps, network graphs) with large geometries

   Filter bottleneck:
   - Every filter change triggers a full database query
   - Cascading filters that trigger multiple queries in sequence

2. Data-layer optimizations:

   Pre-aggregation:
   - Move aggregations from dashboard query time to ETL time
   - Create summary tables at the grain the dashboard needs (daily totals, not individual transactions)
   - Expected improvement: 10–100× faster queries

   Materialized views / extracts:
   - Tableau: extract to .hyper file instead of live connection
   - Power BI: import mode instead of DirectQuery for non-real-time data
   - Looker: persistent derived tables (PDTs)
   - When to use live connection: only when data must be real-time (< 15-minute latency required)

   Caching:
   - Enable dashboard-level query caching
   - Set cache refresh to match data update frequency (no point refreshing every minute if data updates hourly)
   - User-level vs shared cache: shared cache serves the same query result to all users

   Query optimization:
   - Add indexes on filter columns (date, region, product category)
   - Partition tables by date for time-filtered queries
   - Push filters to the query level (not post-query in the viz layer)

3. Dashboard-layer optimizations:

   Reduce chart count:
   - Each chart = one or more queries
   - Remove or consolidate charts that answer the same question
   - Move supporting detail to a second page / click-through

   Lazy loading:
   - Load above-the-fold charts first, load below-the-fold on scroll
   - Show a loading spinner per chart rather than blocking the whole page

   Limit data points per chart:
   - Time series: aggregate to a coarser granularity (weekly instead of daily if trend is what matters)
   - Scatter plots: sample or bin large datasets
   - Tables: paginate or limit to top N rows with a 'load more' option

4. Benchmarks:
   - Target load time: < 3 seconds for first meaningful paint
   - Filter response: < 2 seconds for filter changes
   - Table pagination: < 1 second per page load

Return: bottleneck diagnosis, prioritized optimization list with estimated improvement per action, and implementation steps for the tool specified.