Semi-structured data
Formats such as JSON or XML can carry named fields and nested values, while records may vary in the fields they contain. A parser can extract useful information, but missing, inconsistent or differently defined fields need attention before combining records.
Worked example
One JSON transaction record includes a delivery address while another has only a collection point; both contain a transaction ID and total.
Common mistake
Calling all semi-structured records unstructured simply because fields differ between records.
Where it appears in your exams
| Qualification | Exam | Relationship | Period |
|---|---|---|---|
| ACCA | MA | Direct | September 2026–June 2027 |
| FIA | FMA | Direct | September 2026–June 2027 |