Warehouses
Snowflake Databricks BigQuery Redshift Palantir
Features
Three pillars. One delivered system.
TwiceData is a managed model system — not a tool you log into. Every engagement and every Quarter Stack delivery is built on the same three pillars: curated dbt model packs, lineage-aware change management, and a governed semantic layer.
Pillar 01
Pre-built dbt model packs.
Start with curated SaaS subject areas instead of a blank dbt repo. ARR, retention, product usage, sales pipeline, revenue operations — each shipped as a versioned model pack with tests, documentation, and assumptions written down.
The packs are not a black box. They are real dbt code, ported into your warehouse, reviewed by your team. Once handed off, you own them.
What's in a pack
- Staging + intermediate + mart layers for the subject area
- Schema tests, freshness assertions, snapshot configs
- Documented assumptions (versioned, change-tracked)
- BI adapter views for Looker / Metabase / Mode / Tableau
- Pre-merge lineage gates wired into your CI
Pack · SaaS ARR (v2.4)
stg_subscriptions.sql✓ tested
int_arr_movements.sql✓ tested
fct_monthly_arr.sql✓ certified
fct_arr_cohort.sql✓ certified
mart_arr_dashboard.sql✓ live
docs/assumptions.mdv2.4 · signed
Prebuilt domain packs
The model pack is table stakes. The knowledge graph and MCP are the product.
Every domain pack ships in three layers. A governed model pack gives you tested, lineage-tracked metrics — dbt-first, or SQLMesh / Dataform / pure SQL to match your stack. On top of it we build a domain knowledge graph that captures the entities and relationships your metrics imply. And if you want your AI agents querying it, an MCP server exposes the governed layer as typed, permissioned tools — but that's a choice, not a requirement. Turn it on or leave it off; the pack stands on its own through plain SQL and your existing BI tools. Agent tooling moves fast and that standard may shift within a quarter, so the MCP layer is deliberately a thin, swappable shim — your governed data never moves with it.
14 domain packs ship today, with 437 governed models between them — plus 4 more in preview. Each carries its own graph schema, MCP tool set, and example models you can read before you commit. Browse them all in the model catalog.
What's in a pack
- Governed model pack — staging → intermediate → marts, fully tested, lineage-gated. The dbt foundation, portable to your framework.
- Domain knowledge graph — the entities and relationships your metrics imply (patient → encounter → claim → HCC risk; matter → timekeeper → invoice), traversable by agents and analysts.
- MCP server — typed, permissioned tools over the governed layer, so AI agents answer domain questions without raw SQL or seeing PHI they shouldn't.
- HIPAA-aware handling on the medical pack; row/column governance carried through to every MCP tool.
- Example models shipped in the open — read the SQL before you commit. No black box.
Medical pack — example models
stg_claims.sqlstaging
int_encounters.sqlintermediate
fct_hcc_risk_scores.sqlfact
dim_patient.sqldim
mart_care_gaps.sqlmart
mart_quality_measures.sqlmart
Pillar 02
Lineage-aware change management.
Every model update is impact-scored before merge. Downstream dashboards, semantic entities, and dependent models are flagged automatically — so breakage is caught in CI, not on Monday morning when the CFO opens the wrong dashboard.
This is not a lineage diagram you look at in a slide deck. It is wired into your pull-request flow, gated, and required for merge.
What lineage gates do
- Detect impacted dashboards, models, and semantic entities per PR
- Score breaking-change risk on a 0–10 scale, threshold-blocked
- Auto-comment the PR with the impact list and reviewer suggestions
- Required-status integration with GitHub / GitLab / Bitbucket
- Audit log of every merged change + its impact score
PR · lineage-check.yml
stg_subscriptions.sqlchanged
→ int_arr_movementsaffected
→ fct_monthly_arraffected
→ Looker: ARR dashboarddownstream
Impact score7.2 / 10
StatusGate: required
Pillar 03
Governed semantic layer.
Define certified metrics once and expose them to BI, reverse ETL, and notebooks with role-based access, freshness policies, and audit history built in. The same ARR number that the CFO sees on the board deck is the same number the customer team sees in Looker is the same number the reverse-ETL job pushes to Salesforce.
One definition. Many consumers. Audited every time.
What governance gives you
- Certified-entity model with versioned definitions
- Role-based access (RBAC) per entity and per attribute
- Freshness policies with automated alerting
- Full audit history for every entity read and every definition change
- Reverse-ETL contract: changes propagate or block
- BI adapter exposure: Looker LookML, Cube, Metricflow, custom
Entity · monthly_arr (v4)
ownerFinance Data Team
freshness SLA≤ 4h
RBACfinance, exec, ops
exposed toLooker, Cube, Slack
last auditpassed 2026-05-12
statuscertified
What we work with.
Transform & orchestration
dbt Cloud dbt Core SQLMesh Dataform Dagster Airflow Prefect
BI & Semantic
Looker / LookML Cube Metricflow Metabase Mode Tableau
Cloud & infrastructure
AWS Azure Google Cloud Microsoft Fabric Terraform Pulumi
Legacy modernization
R SAS SPSS Stored procs Excel models
AI augmentation (optional)
Self-hosted LLMs Ollama / vLLM
Security, compliance, and audit.
Identity & access
Your IDP, your rules.
We integrate with whatever you already use for SSO/SCIM. We do not introduce a separate identity surface.
- SSO via Okta, Azure AD, Google Workspace
- SCIM provisioning for service accounts
- Row-level security verified end-to-end
- Audit log of every entity read
Compliance posture
Built for regulated stacks.
We've worked inside SOC2 / HIPAA / GDPR / PCI environments. Engagement scoping accommodates your audit cadence.
- SOC2 Type II workflow alignment
- HIPAA-friendly PII tagging + masking
- GDPR right-to-erasure propagation
- PCI-scoped data exclusion patterns
- Public-sector FedRAMP-adjacent work
Data residency
Data never leaves your perimeter.
TwiceData is delivered code, not hosted infrastructure. Models run in your warehouse account. No data egress, no third-party copy.
- All compute in your cloud account
- Zero data egress by default
- Customer-managed encryption keys
- Region pinning honored
Sample artifacts
What you actually walk away with.
Sample previews of six deliverables. These are sketches of the format — real artifacts ship with your stack-specific data, lineage, and policy details.
Artifact 01 · Stack Diagnostic
Lineage + model-complexity scorecard.
Per-model complexity score (0–10), downstream impact, ownership clarity. The first deliverable of every Stack Diagnostic engagement.
Stack scorecard · v1Page 3 of 18
stg_subscriptions.sql3.2
int_arr_movements.sql7.1
fct_monthly_arr_v2.sql9.4
fct_monthly_arr_legacy.sql9.6
mart_retention_cohort.sql6.8
mart_executive_kpi.sql8.9
Artifact 02 · Quarter Stack
Model pack manifest.
The shipped model packs for a Quarter Stack engagement, with version, owner, and certification status. One row per subject area.
Pack manifest · v4.2Day 91
SaaS ARR packv2.4 · certified ✓
Retention & cohorts packv1.8 · certified ✓
Product usage packv3.1 · certified ✓
Sales pipeline packv2.0 · certified ✓
Revenue operations packv1.3 · certified ✓
Customer success packv1.0 · certified ✓
Artifact 03 · Quarter Stack
Semantic-layer entity catalog.
Certified entities exposed to BI / reverse-ETL / notebooks. Each row: owner, freshness SLA, RBAC roles, exposure surface.
Entity catalog · live62 entities
monthly_arrfinance · ≤4h ✓
cohort_retention_90dgrowth · ≤24h ✓
product_activationproduct · ≤8h ✓
net_revenue_retentionfinance · ≤4h ✓
customer_health_scorecs · ≤12h ✓
pipeline_conversion_ratesales · ≤24h ✓
Artifact 04 · Quarter Stack
Analyst dashboard mock.
A sample of the dashboards shipped against your BI tool. Real dashboards use your data; the format is locked.
Dashboard · ARR overviewLooker / Metabase / Mode
Monthly ARR · last 12 mo
Current MRR$1.84M ↑8.2%
NRR (TTM)118% ↑3pt
Logo retention92.4% ↑1.1pt
Artifact 05 · Stack Diagnostic
Executive risk register.
Risk-scored issues from the diagnostic, prioritized, with severity, blast radius, and a recommended owner. Designed to be readable by your CFO / CIO.
Risk register · v112 items
R-01 ARR variants in 3 pipelinesHigh · Finance
R-02 No freshness alerting on KPIsHigh · Data Eng
R-03 Snowflake spend +60% YoYHigh · CFO
R-04 No lineage gating in CIMedium · Data Eng
R-05 PII tags missing on 14 tablesMedium · Security
R-06 Reverse-ETL no contractMedium · RevOps
Artifact 06 · Stack Diagnostic
30-day remediation plan.
Prioritized action plan tied to the risk register. Each item: owner, effort estimate, dependencies, expected outcome. The plan your team can run after handoff.
Remediation plan · 30-day22 actions
Week 1 · ARR reconciliationFinance Data · 2d
Week 1 · Lineage gates wiredData Eng · 3d
Week 2 · Freshness alertingData Eng · 2d
Week 2 · Top-5 query rewritesData Eng · 4d
Week 3 · PII tagging sweepSecurity · 3d
Week 4 · Reverse-ETL contractsRevOps · 4d
Model packs available
14
Avg time to first metric
< 14 days
Warehouses supported
5
BI adapters
Looker · Metabase · Mode · Tableau
Want to see a pack in your warehouse?
30-minute architecture session. We'll match a model pack to your subject area, scope a fixed-price port, and send a proposal within 48 hours.