Service · Data and platform

Data foundations

One clean data layer from six systems and three versions of Excel.

Relevant to Manufacturing, Service businesses, Education, Growing businesses

The problem

Your data is in six places and three Excel versions. Every report takes a week and two people disagree about the number.

Nothing above works until this works. Most engagements start here, and we say so.

What it costs today

Typical: a week of senior time per month spent assembling reports, and decisions delayed because nobody trusts the number.

This is for you if
  • A report that takes days to assemble, every month.
  • Two systems that give two numbers for the same thing.
  • A plan to do anything else on this page.
What we build
  • A single, clean data layer fed from your existing systems on a schedule.
  • Dashboards people actually use, built with the people who will use them.
  • A data readiness scorecard for every analytical project you might run next.
  • Standard tools (PostgreSQL, scheduled pipelines, an open dashboard tool) that your own IT team can maintain.
How we build itIn this order
  1. 01

    Inventory the sources and their owners

    Every system, export and spreadsheet that holds a number someone relies on, and the person who can explain it.

  2. 02

    Choose the few tables that matter

    Not a warehouse of everything. The ten or fifteen tables behind the decisions you actually make, modelled once and documented.

  3. 03

    Schedule the pipelines

    Idempotent, restartable, with a page that shows when each one last succeeded. A pipeline that fails silently is worse than no pipeline.

  4. 04

    Build dashboards with the people who will use them

    Three to five, not thirty. Each one answers a question someone asked in the first week.

  5. 05

    Document and hand over

    Table definitions, pipeline runbooks, and the readiness scorecard for the projects you might run next.

Data you already haveThis is usually enough to start
  • Everything: ERP, accounting, CRM, LMS, PLC exports, spreadsheets, WhatsApp exports
  • The reports you already prepare by hand
In practice

Illustrative example

From a week-long monthly report to a daily dashboard in 8 weeks

Accounting, the warehouse system and a sales CRM each produced a different sales figure. The owner's monthly review took the finance head a week to assemble and was still argued over.

Read the case study
Typical engagement
Duration6 to 10 weeks
TeamEngineering lead, data engineer
You receiveRunning data layer, documented pipelines, 3 to 5 dashboards, readiness scorecard
PriceFixed price, quoted after a short scoping call
What you own at the end
  • The database, pipelines and dashboards, running on your server or cloud account.
  • Table and pipeline documentation your IT team can act on.
  • The readiness scorecard, one row per project you are considering.

Everything runs in your environment and is handed over with documentation. Nothing stops working if we part ways.

Questions we are usually asked

Is this just dashboards?

Dashboards are the visible part. The value is the clean, scheduled, documented layer underneath, which makes every later project faster.

Which tools?

Boring, well-supported ones your team can run: PostgreSQL, scheduled Python or SQL pipelines, Metabase or similar. No licence trap.

Can our IT team maintain it?

Yes, and the handover includes training. We can also stay on a monthly retainer.

Do we need this before predictive maintenance?

Often a lighter version of it. The assessment tells you how much foundation a specific project needs.

Do we need this before an AI assistant or an agent?

Less than you might think for an assistant, which reads documents. More for an agent, which reads and writes your systems and needs clean masters to match against.

Often combined with

Further reading

Not sure if your data is ready?

Take the free 20-minute readiness check. You get a short scorecard and a plain answer about what, if anything, is worth doing next.

Start the readiness checkTalk to us