Define metrics once. Trust them everywhere.
One source of truth for every number in the business.
Net Revenue
SUM(amount) WHERE status=paid
Churn Rate
churned_mrr / prior_mrr
Active Users (30d)
COUNT DISTINCT user_id, last 30d
One metric definition, everywhere
Define a metric once in the semantic layer and it flows into every Superset chart, AI query, embedded dashboard, and API export automatically.
- Central metric definitions in dbt or Superset virtual datasets
- Change once, propagates to all downstream consumers instantly
- Version-controlled metric history — see who changed what and when
dbt + Superset native
D23 supports both dbt metrics (including dbt Cloud and dbt Core) and Superset's native virtual dataset layer — whichever fits your stack.
- dbt metrics exposed natively in Superset Explore
- Superset virtual datasets for teams without dbt
- Hybrid mode: dbt for modelled metrics, Superset for ad-hoc
AI text-to-SQL grounding
The AI generates SQL against your semantic layer, not the raw warehouse schema — so it uses correct metric logic and respects business rules.
- AI queries routed through the semantic layer automatically
- Metric names in plain English map to correct SQL
- No hallucinated table names or wrong join paths
Works with your warehouse and your cloud
How semantic layer works
- 1
Audit your metrics
D23 catalogs your existing dashboards and finds every divergent definition of each key metric.
- 2
Define the canonical version
Your data team and D23 agree on the correct SQL logic for each metric and encode it in the semantic layer.
- 3
Deprecate the divergent datasets
Old ad-hoc datasets are replaced with references to the semantic layer. Existing dashboards are migrated.
- 4
Every tool reads the same layer
Superset charts, AI queries, embedded analytics, and exports all query through the semantic layer — one truth.
See it in context
The board meeting discrepancy
Before
The CFO's revenue number is $2M higher than the CRO's. Both have data to back them up. The meeting derails.
With D23
Both dashboards query the canonical "Net Revenue" metric from the semantic layer. The number matches everywhere, every time.
The policy change
Before
Finance changes the revenue recognition policy. A data analyst updates 23 separate dashboards over three days. Some are missed.
With D23
The analyst updates the "Net Revenue" definition in the semantic layer once. Every dashboard and AI query reflects the change immediately.
What teams use it for
Single source of metric truth
Encode revenue, churn, LTV, and every other key metric once — and eliminate dashboard disagreements permanently.
dbt metrics integration
D23 connects your existing dbt semantic layer to Superset and the AI text-to-SQL engine with no extra work.
AI-ready schema
The semantic layer gives the AI correct table names, metric logic, and join paths — so text-to-SQL generates accurate SQL every time.
The numbers behind modern BI
You don't have to take our word for it. Here's what analysts and data teams are reporting right now.
$8.7B
global BI and analytics market revenue in 2025, growing to $14.9B by 2030 as self-serve BI adoption accelerates.
73%
of organizations say data accessibility is the top barrier to becoming data-driven, per Forrester.
5×
faster time-to-insight for teams using self-serve BI versus those relying on a central data team for every query.
Most teams cut their BI cost by half and ship dashboards in days, not quarters.
D23 estimate, based on typical data-team workloads: hours saved on Superset ops, faster dashboard delivery, and self-serve analytics that no longer requires a dedicated analyst for every question. Your mileage depends on warehouse size and how many teams need access to data.
It already works at this scale
Not a demo. A team in the same kind of work, with results they published.
Nielsen
Financial Services · analytics
Nielsen migrated its enterprise BI stack to Apache Superset, reducing per-seat BI licensing costs by more than 60% and enabling its data teams to ship new dashboards in days instead of weeks.
60%+
BI licensing cost reduction
days
to ship a new dashboard
1 platform
replacing multiple BI tools
The strongest results come from teams with a connected warehouse, defined metrics, and dashboards their stakeholders actually use. That is exactly what D23 delivers.
1×
define a metric, use it everywhere
One definition of revenue, churn, and every other metric — trusted by every team.
Explore more of D23
Managed Apache Superset
Zero-downtime upgrades. No infra tickets. Just dashboards.
Embedded analytics
Your brand. Your data. Invisible infrastructure.
AI analytics
Natural language to insight in seconds.
Self-serve BI
No SQL. No tickets. No waiting.
Security & governance
SSO, row-level security, and audit logs — ready on day one.
Turn every team into a data team.
Get managed Apache Superset, the dashboards your business needs, and AI on top, without hiring a data team.