Data foundations
software engineering
Data foundations
Reports are only as good as what sits underneath them. We model the core things your business deals with, agree who owns them, and build the pipelines that keep them current.
In practice
what you end up working with
| Dataset | Owner | Freshness |
|---|---|---|
| Customers | Customer team | Current |
| Accounts | Finance | Current |
| Products | Product team | Two days old |
| Campaigns | Marketing | Needs owner |
The problem
Two dashboards give two different answers to the same question.
What it usually looks like.
Reports disagree, definitions differ between departments, and nobody owns the core data. Decisions wait while people argue about whose number is right.
When to ask for it
- Two reports give different answers to the same question
- Data is copied between systems by hand or by fragile scripts
- You are preparing for analytics, automation or AI, and the data underneath is not ready
Scope
agreed in writing before work starts
What the work covers.
In scope
- A shared glossary and a model of the core things your organisation deals with
- Ownership and quality rules for that data
- Ingestion and transformation pipelines that keep it current
- Reporting-ready datasets with documented definitions
- Personal information handled in line with POPIA
Not included
- Building every report and dashboard (we prepare the data and the first few)
- Selling or operating a data platform licence
Approach
small steps, each one reversible
How the work runs.
- Start from the decisions the data has to support
- Agree definitions and owners before building pipelines
- Build pipelines with tests on the data, not only on the code
- Publish datasets with their definitions, so reports agree by design
Every engagement also includes decision records, tested releases, documentation you own and a planned handover. How we work
Deliverables
each one ends with something you keep
What you keep.
Deliverables
- A shared glossary and data model
- Ownership and quality rules
- Reliable ingestion and transformation pipelines
- Reporting-ready datasets
What it is for
- One answer to each important question, with a named owner
- Data that is current without manual copying
- Foundations that analytics and automation can build on
Related
Where this shows up.
Patterns
- Connecting fragmented services C: Illustrative
Often paired with
- Cloud and integration architecture Design how systems connect, where they run and what happens when parts fail.
- Product engineering Build web products and internal tools that people want to use.
The usual first step A landscape review : A short, fixed-scope look at your systems that ends with a map and a recommendation. You decide what happens next.
Next step
start with the problem, not the service
Bring us the tangled part.
Describe the situation in your own words. We will tell you where we would start, including when the answer is a small piece of work.