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Fieldnote Learning Centre — Linked operating model

Linked operating model for Fieldnote Learning Centre. 72 records across 5 linked tables; no duplicate primary keys or missing references. Enrollments=18.00 records; Passed completions=9.00 learners; Available course seats=30.00 seats.

Preview, first 50 linesjson
{
  "id": "business-education-training",
  "slug": "education-training",
  "title": "Fieldnote Learning Centre",
  "industry": "education",
  "description": "Fictional course capacity, enrollment, completion and assessment records for LMS mappings and reporting.",
  "workflows": [
    "enrollment",
    "completion",
    "assessment",
    "attendance",
    "learning-materials"
  ],
  "asOf": "2026-09-08",
  "source": "deterministic-synthetic",
  "tables": {
    "courses": {
      "primaryKey": "course_id",
      "foreignKeys": [],
      "rows": [
        {
          "course_id": "COURSE-1",
          "name": "Spreadsheet basics",
          "capacity": 10,
          "pass_score": 70
        },
        {
          "course_id": "COURSE-2",
          "name": "Customer service",
          "capacity": 10,
          "pass_score": 70
        },
        {
          "course_id": "COURSE-3",
          "name": "Workshop safety orientation",
          "capacity": 10,
          "pass_score": 70
        }
      ]
    },
    "learners": {
      "primaryKey": "learner_id",
      "foreignKeys": [],
      "rows": [
        {
          "learner_id": "LEARN-01",
          "name": "Sample learner 1"
        },
        {
          "learner_id": "LEARN-02",
613 lines total: download for the full file.

Specifications

Kit
education-training
Industry
education
Schema Version
1
Synthetic
true
As Of
2026-09-08
Records
72
Tables
5

Testing contract

Expected to pass
Scenario
Use linked operating model in the Fieldnote Learning Centre enrollment, completion, assessment, attendance, learning-materials workflow.
Expected result
72 records across 5 linked tables; no duplicate primary keys or missing references. Enrollments=18.00 records; Passed completions=9.00 learners; Available course seats=30.00 seats.

What is a .json file?

JSON (JavaScript Object Notation) is a lightweight, text-based data-interchange format representing objects, arrays, strings, numbers, booleans, and null. It is language-independent, human-readable, and the dominant format for web APIs and configuration. It requires a single well-formed root value.

How to use this file

Use an example JSON file to test parsers and serializers, schema validation, Unicode and number-precision handling, and API request or response processing.

How to use this file for testing

“Fieldnote Learning Centre — Linked operating model” is a deterministic Novus Examples fixture for Data import. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.

Documented properties for this file: 72 records. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.

Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such, expect parsers to fail loudly rather than silently accept them.

Data fixtures document their exact quirks (delimiters, encodings, null handling, schema, and row counts) in the spec table. Point your parser or importer at the file and assert it handles the documented edge cases; clean and deliberately-messy siblings make before/after diffs straightforward.

Code examples

import json

with open("operating-model.json") as f:
    data = json.load(f)
print(type(data), len(data))

Generated by generation/business_fixtures.py. Free for any use, no attribution required, license.