> For the complete documentation index, see [llms.txt](https://experience-digital-transform.gitbook.io/experience-digital-transformation/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://experience-digital-transform.gitbook.io/experience-digital-transformation/analytics/technical-specifications/7.-data-structures.md).

# 7. Data Structures

The key data objects managed by the Analytics Building Block, their primary lakehouse layer, and their key attributes.

{% hint style="info" %}
🗄️ **Looking for field-level schemas?** Full JSON Schema definitions for the objects below live in the OpenAPI appendix (Section 13).
{% endhint %}

The following table defines the key data objects managed by the Analytics Building Block. These data structures are generic; the education-specific rows illustrate how they carry school, teacher, student, and learning outcome data types when deployed for national education use cases. Full OpenAPI schema definitions are provided in the relevant appendix.

| Data Object                | Description                                                                                                                                                    | Primary Layer   | Key Attributes                                                                                                                     |
| -------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------- | ---------------------------------------------------------------------------------------------------------------------------------- |
| IngestionPayload           | Harmonised dataset received from an upstream BB or file upload.                                                                                                | Bronze → Silver | source\_system\_id, schema\_version, ingestion\_timestamp, record\_count, receipt\_token                                           |
| GoldenRecord               | Deduplicated, reconciled master entity record in the Silver layer.                                                                                             | Silver          | entity\_type, entity\_id, attributes\[], version, lineage\_ref\[]                                                                  |
| SourceEstimate             | One source's estimate of a quantity for an analytical unit (N per unit). For climate: a bottom-up or observed estimate for a sector × zone × sub-cell × cycle. | Silver          | unit\_key, source\_id, value, unit\_of\_measure, confidence, method, blind\_spots, kind (bottom\_up \| observed)                   |
| ReconciliationResult       | The gap analysis for an analytical unit across its sources.                                                                                                    | Silver          | unit\_key, run\_id, sources\_compared\[], discrepancy, threshold, flag\_status                                                     |
| ReconciliationDecision     | Append-only, governed decision designating the authoritative value for a unit.                                                                                 | Silver          | unit\_key, selected\_source \| blend\_rule, designation (official \| supplementary), rationale, actor\_id, timestamp               |
| DataMart                   | Pre-aggregated analytical dataset in the Gold layer (e.g. a validated GHG inventory, an NDC-tracking mart).                                                    | Gold            | mart\_id, domain, aggregation\_dimensions\[], refresh\_schedule, schema\_version, expiry                                           |
| GeospatialAsset            | STAC-indexed raster or vector asset for spatial and Earth-observation analysis.                                                                                | Silver / Gold   | asset\_id, geometry, crs, resolution, temporal\_extent, stac\_item\_ref                                                            |
| QueryRequest / QueryResult | Natural-language or structured query and its access-controlled result.                                                                                         | All             | session\_token, query\_text, target\_layer, language; query\_id, result\_set, row\_count, execution\_ms, security\_policy\_applied |
| AuditLogEntry              | Immutable record of a data-access or decision event.                                                                                                           | Log Store       | log\_id, preceding\_hash, entity\_ids, fields\_read, user\_id, role, timestamp, justification                                      |
| TriggerRule                | Threshold or event condition initiating a proactive workflow or webhook.                                                                                       | Gold            | rule\_id, condition\_expression, target\_mart, signal\_endpoint, version, approved\_by                                             |
| MLModel                    | Versioned predictive model deployed as a scoring microservice.                                                                                                 | Model Registry  | model\_id, version, training\_dataset\_ref, accuracy\_metrics, deployment\_endpoint, status                                        |
| PipelineRun                | Execution record for a transformation pipeline across layers.                                                                                                  | Orchestrator    | run\_id, pipeline\_id, start\_time, end\_time, records\_in, records\_out, records\_rejected, status                                |


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://experience-digital-transform.gitbook.io/experience-digital-transformation/analytics/technical-specifications/7.-data-structures.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.