Data

Data & analytics

From 'we have data somewhere' to 'we run on data'. Platforms, pipelines, dashboards you can audit.

Data platforms, ETL pipelines, BI dashboards, embedded analytics, and data governance.

What's inside

Capabilities

Data platform

Snowflake / BigQuery / Postgres-as-DW — pick the right one, set it up correctly, hand it over.

Pipelines & ETL

Fivetran / Airbyte / dbt for the modern stack. Custom Python where the modern stack falls short.

BI dashboards

Metabase, Looker Studio, Power BI — chosen for the team that'll maintain them.

Embedded analytics

White-labelled dashboards inside your customer-facing app, with row-level security.

Data governance

Catalogue, lineage, access control. ISO 27001 / UAE PDPL aligned.

Real-time analytics

When batch isn't fast enough — Kafka, ClickHouse, materialised views.

How we deliver

A four-stage engagement.

  1. 01

    Inventory

    What data do we have, where does it live, who already owns each source?

  2. 02

    Model

    Source → staging → marts. dbt-style transformations with tests.

  3. 03

    Surface

    Dashboards and embedded views built for the question, not the data.

  4. 04

    Govern

    Catalogue, lineage, access reviews, and a documented data risk register.

Why this matters

What you get with us.

Numbers you can audit

Every metric traces back to a SQL query in version control. No "magic spreadsheets".

Self-serve

Your team queries the warehouse. We don't become a bottleneck.

Right-sized stack

We do not push Snowflake on a 10GB warehouse. The stack matches the data volume.

PDPL / GDPR aligned

PII handling, retention policies, and access logging built in.

FAQ

Common questions about this service.

  • How small a data project is too small?

    None. We have shipped useful warehouses on 10GB of data. The right tool changes; the discipline doesn't.

  • Snowflake or BigQuery or Postgres?

    Postgres-as-warehouse for under ~100GB. BigQuery / Snowflake above that, picked on team familiarity and cost model.

  • Do you replace our analytics team or augment it?

    Either. We have run analytics for clients without one, and embedded as senior engineers when the team exists.

  • How do you handle PII?

    Tag at ingestion, encrypt at rest, mask in non-production environments, audit access. Default modules implement all four.

Let's talk

Tell us about your project.

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