Automatizav1
ANALYTICS · DATA · OBSERVABILITY

Production data pipelines for teams that ship in dbt

Contracted ingestion, modeled warehouse, dashboards on a single semantic layer. Postgres, Snowflake, BigQuery — wired in week 2, lifted in week 6.

Book a stack reviewSee the platform
Freshness · p95 target < 5 minTested on every PR · contracts on every mart
workspace/dashboard/revenue
Revenue · last 12 days · USD
Target $10kDec 08$12,420

Recently shipped to

  • Tier-1 European sportsbook
  • LATAM marketplace
  • Brazilian fintech
  • EU-licensed lottery operator
  • Subscription DTC brand
  • Regional bank — partner project

Connects to your stack

Postgres
Snowflake
BigQuery
Segment
Stripe
Redshift

What we do

End-to-end business intelligence, from raw data to decisions

We combine data engineering, analytics, and visualization into a single operation. We measure what matters, cut noise, and deliver clear answers for revenue, product, and infrastructure teams.

  • Unified data models on a governed warehouse
  • Executive and operational dashboards
  • Pipelines with automated tests and contracts
  • Observability, lineage, and freshness SLAs
DATA FLOW

From raw source to activation in one pipeline

Every byte is traceable. Every metric is defined once. No spreadsheets in the middle.

01 · SOURCES
Sources
DBs · SaaS · events
02 · PIPELINE
Pipeline
ELT · tests · dbt
03 · WAREHOUSE
Warehouse
modeled · governed
04 · ACTIVATION
Activation
BI · reverse-ETL

Services

Three tracks. One contracted data operation.

Pipelines, BI, analytics engineering. Each ships with an owner, a freshness contract, and a public scope. No black boxes, no spreadsheet detours.

SRV-01

BI & Dashboards

Data warehouses, ETL pipelines, and executive visualizations that unify sources and expose trends in real time.

  • Dimensional modeling and data warehouse
  • Monitored ETL/ELT pipelines
  • Executive and operational dashboards

SRV-02

CRM Analytics

Advanced segmentation, LTV, churn, and cohorts to guide marketing, sales, and retention with evidence.

  • Customer segmentation and scoring
  • LTV, churn, and cross-sell models
  • Multichannel attribution and cohorts

SRV-03

Ops & Infrastructure Analytics

Cost, performance, and availability observability for technology teams that need to prove ROI.

  • FinOps and cloud cost optimization
  • SLIs, SLOs, and performance monitoring
  • Capacity and efficiency reporting

Platform · Quality

Four axes your team can audit

Versioned models, tested on every PR, observable in production. The number on the dashboard is the number under contract.

4 quality axes · versioned · tested · observable
FEAT-01

Cohort & retention models

Acquisition cohorts, D1/D7/D30 curves, and retention by channel — defined once in the semantic layer.

FEAT-02

Operational dashboards

Live KPI trees on the modeled warehouse. Owner per dashboard, contract per metric.

FEAT-03

Typed connectors

Postgres CDC, Snowflake, BigQuery, Stripe, Segment, GA4. Schema registry on every source.

FEAT-04

Tested at warehouse scale

Validated up to 200M rows/day on Snowflake X-Large. Backfills, watermarks, and SCD-type-2 covered.

PLATFORM

An analytics stack you can trust end-to-end

Every layer is versioned, tested, and observable. Data quality is not a report at the end, it is a contract at every step.

Governed models

dbt-first, tested, versioned.

Self-serve BI

Queryable by analysts and ops.

Observability

Freshness, contracts, lineage.

QUERY PLAYGROUND

Your data, queryable the moment it lands

Real SQL on modeled tables, no BI middleware in the way.

queries / revenue_anomaly.sqlrun
1-- Monthly recurring revenue with anomaly flag
2SELECT period, SUM(amount) AS revenue,
3 revenue / LAG(revenue) OVER (ORDER BY period) - 1 AS growth,
4 CASE WHEN growth > 0.15 THEN 'alert' ELSE 'ok' END AS status
5FROM fct_revenue
6WHERE period >= '2024-01-01'
7GROUP BY 1 ORDER BY 1 DESC;
periodrevenuegrowthstatus
2024-12$184,320+12.4%ok
2024-11$163,880+18.7%alert
2024-10$138,120+6.2%ok

How we work

An iterative, measurable, auditable process

STEP-012024-12-08 14:02:11 UTC

Audit & Discovery

We map sources, KPIs, stakeholders, and gaps. Hypotheses and measurable goals are set before any code is written.

STEP-022024-12-12 09:41:03 UTC

Implementation & Integration

We build pipelines, models, and dashboards integrated with your systems, with automated testing and data governance.

STEP-032024-12-19 16:28:57 UTC

Monitoring & Optimization

We track metrics in production, refine models, and evolve the platform in short continuous-improvement cycles.

Who we work with

Operators, not committees

We partner with the small group inside an org that has to defend the number — Heads of Data, VP Engineering, Head of Growth — and ship the modeling, the dashboards and the alerts they actually need.

  • Heads of Data & analytics

    Owns the warehouse, the metric tree, and the on-call rotation.

  • VP Engineering / CTO

    Wants typed pipelines, idempotent jobs, and observable runs.

  • Heads of Growth / RevOps

    Reads cohort retention, ROAS, payback weekly. Tired of broken funnels.

  • Heads of CRM & retention

    Segmentation, scoring, lifecycle — without the manual SQL.

  • BI engineering teams

    Wants modeled marts, not a fresh BI tool every quarter.

  • Founders evaluating a data stack

    Choosing between in-house, agency, and a tool. We ship like a tool.

GLOSSARY

Terms we use, so everyone speaks the same language

A shared vocabulary between data, product, and revenue teams.

Total sales & marketing spend divided by customers acquired in the period.

CAC = (S&M spend) / (new customers)

Contact

Tell us your stack. We'll reply in one business day.

Engineering reads every request — no SDR in the middle. Send your warehouse, your pain, and one or two metrics you'd like to fix.

emailhello@automatizaanalytics.com.br

sla< 1 business day