SQL to Dashboard Pipeline Guidebook
🎯 Purpose
This guidebook helps analysts design SQL that flows cleanly into dashboards or BI tools like Looker Studio. It focuses on writing performant, readable queries that produce stable, shareable, and visualization-ready outputs.
🧱 1. Use Views or Saved Queries
| Reason |
Benefit |
| Reusable logic |
Don't repeat joins, filters, or groupings in dashboards |
| Pre-aggregation |
Reduces dashboard lag + query costs |
| Easier version control |
Track in Git or docs |
🧪 Best Practice
CREATE OR REPLACE VIEW clean_dashboard_metrics AS
SELECT
DATE(event_date) AS date,
region,
COUNT(DISTINCT user_id) AS active_users,
SUM(spend) AS total_revenue
FROM project.dataset.raw_events
WHERE event_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 90 DAY)
GROUP BY date, region;
🔍 2. Column Naming Conventions
| Pattern |
Example |
| snake_case |
total_users, avg_order_value |
| readable dimensions |
region, channel, cohort_month |
| metric clarity |
revenue_usd, session_count |
✔️ Avoid ambiguous labels like value, amount, type
📊 3. Output Shape by Dashboard Type
| Dashboard Layer |
SQL Output |
| KPI Cards |
One row per date or region with metrics |
| Trend Charts |
Time series format (date + metric) |
| Cohort Tables |
cohort_id + time_step + value |
| Tables |
Clean, joined, deduplicated flat format |
🧪 4. Aggregation Strategy
| Recommendation |
Why |
| Pre-aggregate in SQL |
Faster, simpler dashboards |
| Apply CASE for flags |
Easy to chart segment slices |
| Create bucket fields |
For histogram/facet charts |
CASE
WHEN spend > 1000 THEN 'high spender'
WHEN spend > 100 THEN 'moderate'
ELSE 'low'
END AS spender_segment
⛔ 5. Where Not to Filter in SQL
| Filter Type |
Apply In SQL? |
| Security filter (e.g. internal only) |
✅ Yes |
| Dashboard dropdown filter (e.g. channel) |
❌ No (Let dashboard do it) |
| Date scoping (fixed vs dynamic) |
⚠️ SQL for heavy views, UI for user needs |
🗂️ 6. Export-Ready Tips
| Format |
Tool |
.csv |
Use for snapshots, simple metrics |
.json |
For API-pull dashboards or audit logs |
| Materialized View |
Fastest dashboard backend |
| Temp Table |
Testing only — don’t use in prod dashboards |
✅ Dashboard Pipeline Checklist
- [ ] SQL view created and named cleanly
- [ ] Column names readable and scoped to dashboard
- [ ] Output shaped by dashboard (KPI/trend/table)
- [ ] Pre-aggregation, flags, CASE fields added
- [ ] Filters pushed to dashboard unless business-critical
- [ ] Export tested for
.csv or view refresh
💡 Tip
“Dashboards shouldn’t decode SQL logic — SQL should deliver dashboard-ready answers.”