Pack · Data · The Constellation

From raw data to decisions.

We design the database, build the pipeline and ship the dashboards — the full lifecycle, governed and monitored.

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Pipeline stages

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Data lineage

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Freshness SLA

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Silent failures

The data journey

Model → Ingest → Transform → Store → Visualise.

01

Model

Schema & database design — relational and dimensional.

02

Ingest

Connectors for sources, APIs, files and events.

03

Transform

ETL/ELT with orchestration and data-quality tests.

04

Store

Warehouse or lakehouse, modelled for query.

05

Visualise

Dashboards and self-serve analytics.

What we build

Three pieces, one pipeline.

Database conception

Relational and dimensional modelling, constraints, row-level security.

Pipelines

Batch & streaming ETL/ELT, orchestration and data-quality tests.

Visualisation

Dashboards, self-serve analytics and KPI reporting.

Governance & quality

Trustworthy by construction.

Access control

Least-privilege access and row-level security on sensitive data.

Lineage

Traceable transformations — you know where every number came from.

RGPD handling

Personal data classified, minimised and retained by policy.

Monitoring

Alerting on freshness, volume and quality across pipelines.

The stack

Proven tools.

PostgreSQLBigQuerydbtAirflowKafkaMetabase

Use cases

What it unlocks.

One warehouse, every source

Consolidate scattered systems into a single, modelled source of truth.

Self-serve KPI dashboards

Give teams trustworthy numbers they can explore without engineering.

Near-real-time events

Stream operational events into analytics with low latency.

FAQ

Questions, answered.

Yes. We adapt to your stack — Postgres, BigQuery, Snowflake or a lakehouse — rather than forcing a rebuild.

Ready to make your data work?

From a first warehouse to a real-time pipeline — tell us where you are.