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Service 03 / 04

Data Solutions

When reports take hours and no two teams agree on the figures, we rebuild the data layer: ingestion, modelling, quality and the dashboards on top.

03 / 04
Pipelines · Warehouse · BI
What we build

One source of truth, refreshed while you sleep.

D1

Ingestion pipelines

Batch and streaming from SaaS APIs, databases, files and events, with schema checks and alerts.

D2

Warehouse & modelling

Clean, documented models in BigQuery, Snowflake or Postgres. dbt-tested and versioned.

D3

Dashboards & reporting

Metabase, Looker or custom, designed around the decisions people actually make.

D4

Data quality

Freshness, volume and anomaly monitoring so bad data is caught before the board meeting.

D5

AI-ready data

Embeddings, feature tables and retrieval layers so your AI work starts on solid ground.

D6

Migration & consolidation

Merge the eleven spreadsheets and three legacy systems into one platform.

Typical outcomes

What changes
in eight weeks.

Indicative ranges from past engagements. We scope a target number with you before we start.

4h→9m
Reporting cycle time
Manual month-end assembly replaced by scheduled, tested pipelines.
1
Definition per metric
Revenue, churn and active users mean the same thing in every room.
11→1
Sources into one platform
Consolidated, documented, with lineage you can follow.
Stack we reach for

Boring, proven infrastructure by default. The right model for each step. Nothing you couldn't hire for.

dbtBigQuerySnowflakeAirflow / DagsterPostgresMetabasePythonKafka

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