05 / SQL Transformations
Book a demo →Everything is queryable.
All logic lives in SQL. Every metric, cohort, and opportunity signal is defined as a view — not hidden in compiled code.
For:BD leadersProductData teams
Canonical views
cost_of_care_by_cohort_and_geoprovider_performance_by_conditionutilization_patterns_by_site_of_carequality_vs_cost_frontierreimbursement_alignment_tablesreadmission_rates_by_drgscreening_gaps_by_populationadherence_by_therapeutic_class
Sample query
-- Find HRRs where CHF readmissions exceed benchmark -- AND CCM/RPM utilization is below the 25th percentile. SELECT geo.hrr, geo.hrr_name, perf.readmission_rate_30d, perf.benchmark_rate, util.ccm_utilization_pct, util.rpm_utilization_pct, cost.avoidable_cost_pmpm FROM provider_performance_by_condition AS perf JOIN utilization_patterns_by_site_of_care AS util USING (hrr, condition) JOIN cost_of_care_by_cohort_and_geo AS cost USING (hrr, cohort_id) JOIN geography AS geo USING (hrr) WHERE perf.condition = 'CHF' AND perf.readmission_rate_30d > perf.benchmark_rate AND util.ccm_utilization_pct < 0.10 ORDER BY cost.avoidable_cost_pmpm DESC LIMIT 25;
Why SQL-native matters
- — Transparent: any analyst can read and audit the logic
- — Modifiable: customer teams extend without filing tickets
- — Compatible: works with any SQL-capable tool or AI agent
- — Portable: the same view runs on DuckDB, Postgres, or your warehouse
What this means for you
Your analysts can fork a view, adjust the definition for your business, and ship a new opportunity signal in an afternoon — not a quarter.
See this in your data
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