Data engineering and analytics

One set of numbers your whole business can trust.

Pipelines that bring your data together, warehouses modelled around your business, checks that catch bad data early, and dashboards and forecasts people actually use.

What we do

What this covers.

  1. 01

    Data pipelines

    Scheduled and event-driven loads from your ERP, CRM, apps, files and APIs, with history kept and failures alerted.

  2. 02

    Warehouses and models

    Snowflake, Redshift or BigQuery, modelled with dbt so each metric has one written definition.

  3. 03

    Data quality

    Tests on every load that flag missing, late or odd data before it reaches a report.

  4. 04

    Dashboards and forecasting

    Dashboards, scheduled reports and forecasts for the people who make decisions.

An operations dashboard: revenue against target, regional performance, top-moving products and data source checks.

Typical projects

The kind of work we take on.

  • A weekly management pack that builds itself
  • A sales, stock and margin warehouse across stores and channels
  • An operational data platform for plant or fleet data
  • Moving reporting off spreadsheets onto a governed warehouse
  • Demand or revenue forecasting
  • A data audit: where every number comes from and who relies on it

Technology

Typical stack.

  • Snowflake
  • dbt
  • Python
  • PostgreSQL
  • Amazon Redshift
  • Google BigQuery
  • Azure SQL
  • Azure Synapse
  • AWS Glue
  • Dashboards
  • and whatever fits your stack

How we work

Small steps, each with a clear decision.

  1. Discover

    A short discovery to agree the problem, the users and what a good result looks like.

  2. Pilot

    A working first version on your real data or with real users, at a fixed scope and price.

  3. Build

    If the pilot earns it, the full system, released in small steps your team can try.

  4. Run or hand over

    We keep it running and improving, or hand it over with the code and documentation.

Ready-made solutions

Start from something we have already built.

Where one fits, a ready-made solution gets a project to a working first version sooner.

All ready-made solutions

Questions

What people ask first.

Which tools do you use?

Whatever fits your size and budget. Often a cloud warehouse with dbt and a standard dashboard tool, rather than a large platform.

Do we have to move everything at once?

No. We start with the report that hurts most, make it automatic and trusted, then extend.

Start with a conversation

Tell us what's slowing your operation down.

A 30-minute call with the people who would build it. You leave knowing whether a pilot makes sense, and what it would cover.