Requirements, governance and enterprise review
Example-driven data-quality specification
Data-quality rules as examples: the checks a dataset must pass, stated against concrete records.
ddn@1New DDN source
Why use it?
Rules stated on real examples get implemented; rules stated in prose get admired.
When it helps
Defining acceptance for a data product or feed.
How to read it
- Each rule names the check, the records it guards, and what failure means.
- A rule without a severity is an opinion.
What you need
- The dataset
- The rules per field/record
- Failure severities
Things to check
- Do not write rules you cannot point at a record for.
- Do not make everything a warning — then nothing is.
Scope of this diagram
Specification documentation; the checks are stated, not executed by this view.
Work with the converted example
- Open the viewer and select
diagram. Inspect the rendered view and its source. - Open the designer. Keep the selected profile and inspect its legal palette and property controls.
- Change one displayed title or an appropriate data value. Apply the edit and check the resulting diagram.
- Run the verifier and review its diagnostics before moving complete content into review.
- Download your edited DDN source to retain the change.
The example uses the indentation-based ddn-next-1 dialect. The language guide explains reusable definitions, dotted data rows and explicit property blocks.