Source inventory
Every system, what it holds, how it can be read, and what it does when you read it too often.
Software development
Data engineering & integration
Getting data out of the systems holding it hostage and into one place that can be queried and trusted, with schema contracts and backfills that do not quietly corrupt last year's numbers.
The situation
Two reports, two answers, one meeting
The symptom is a disagreement about a number. The cause is usually that three systems each hold part of the truth, joined by hand in a spreadsheet each month, with the joining logic living in somebody's head.
Fixing it is unglamorous and highly valuable: agree the definitions, land the raw data reliably, transform it in one reviewable place, and make every load reproducible so a correction does not rewrite history unpredictably.
Scope
What the work includes
Ingestion with contracts
Batch or event-driven loads that validate shape on arrival and fail loudly rather than absorbing bad rows.
Transformation in one place
Business logic as reviewed, tested SQL or code, not as a formula in a workbook on a shared drive.
Replayable backfills
Historical corrections that can be re-run for a specific window without side effects on everything else.
Warehouse and access model
A schema analysts can navigate, with permissions that respect what each role should see.
Freshness monitoring
Alerts when a feed stops arriving, before the Monday report is wrong rather than after.
1
Definition per metric, agreed in writing
100%
Loads replayable for a chosen window
0
Business logic left in spreadsheets
Deliverables
What you are left holding
Every engagement ends with artefacts you own outright, whether we continue together or not.
- Pipeline code and infrastructure as code
- Documented schema and data dictionary
- Freshness and quality monitoring
- Backfill procedures
Typical stack
What we build it with
Chosen for support horizon and hiring pool, not novelty. If your team already runs something equivalent, we will use yours.
PostgreSQLdbtPythonEvent streamingBI dashboards
Questions
What clients ask first
We already have a BI tool. Do we need this?
A BI tool renders whatever it is given. If two dashboards disagree, the problem is upstream of the tool, and that is the layer we work on.
Can you work with a legacy system that has no API?
Usually: through a read replica, a database view, an export, or a scheduled extract. We will tell you which options are safe and which will put load on a production system.
Who owns the definitions afterwards?
You do, and that is the point. We write them down, put them under review, and make sure changing one is a visible decision rather than an edit nobody noticed.
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Is this the problem you have?
Describe it in three sentences and we will tell you what the first two weeks would look like.