Definition
Structured data is data organized according to a predefined, explicit schema (fixed fields, defined data types, consistent format) such as an asset register's columns or a work order's date, cost, and status fields. Its explicit organization makes it directly queryable and analyzable by standard tools, unlike unstructured data, which has no such predefined schema.
Key facts
- Organized by a predefined, explicit schema (fixed fields and types) not free-form content.
- Directly queryable and analyzable by standard database tools, without additional processing to extract meaning.
- Typical maintenance examples include asset register fields, work order status and cost data, and time-series sensor readings.
- Distinct from unstructured data, which lacks this predefined organization (free-text notes, images, PDF documents).
How does Structured data work in maintenance?
Structured data conforms to a predefined, explicit schema: a specific set of fields, each with a defined type (a date, a number, a category from a fixed list), such as the columns of an asset register or the fields of a work order, making it directly filterable, sortable, and analyzable.
How it differs from unstructured data
Unstructured data (free-text maintenance notes, photos, PDF manuals) has no predefined schema, requiring additional processing (such as computer vision or natural-language techniques) to extract usable, structured information from it. Structured data is already organized in a way standard analytical tools can work with directly.
FAQ
Frequently asked questions
What characterizes data with explicit structure?
Structured data is characterized by conformance to a predefined, explicit schema (fixed fields and types) making it directly queryable and analyzable, distinct from unstructured data, which lacks such a schema.
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