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Reference

This section records the exact dbt resources, configuration names, relation grains, command signatures, and security contracts in bricksgdpr.

Use Tutorials for guided lessons, How-to guides for task-oriented instructions, and Explanation for design context.

Project inventory

Resource type Count Notes
Models 29 8 views, 14 tables, and 7 ephemeral models
Seeds 4 Deterministic synthetic source extracts
SQL functions 3 Created in the fixed priva_internal schema
Local macros 7 Includes catalog, schema, key, case, and access-control macros
Data tests 251 214 generic tests and 37 singular tests
Unit tests 2 Both target the service-resolution classifier
Sources 0 Seeds are referenced directly with ref()
Snapshots 0 Current-state relations use full replacement
Exposures, metrics, semantic models 0 No semantic-layer resources are defined
Named selectors 0 Selection uses resource names, graph operators, and tags

Counts describe the checked-in project manifest. Fixture result counts apply only to the checked-in synthetic seeds.

Pages

Page Lookup subject
Project layout Repository paths and dbt resource locations
Configuration Environment variables, dbt variables, and fixed names
Commands Local, dbt, identity, acceptance, and bundle commands
Catalogs and schemas Catalog placement, schema names, and default readers
Sources and Layer1 Seeds, typed staging views, and raw quarantine tables
priva_map Raw-to-pseudonymous mapping relations, tags, and masks
Layer2 Key boundaries, classifiers, accepted tables, and reason codes
Layer3 and case views Dimensions, facts, and controlled readable views
Functions and macros SQL function and Jinja macro signatures
Tests and selectors Test counts, enforced invariants, tags, and selection forms
Access control Persona matrix, grants, masks, and trusted boundaries
Identity and acceptance Identity modes, required variables, and task-state contract
Bundle job Databricks Asset Bundle target and job definition
Glossary Project-specific terms and abbreviations

Scope

bricksgdpr is a Databricks demonstration of pseudonymization, controlled resolution, access metadata, quarantine, and logical current-state deletion. It is not a GDPR compliance certification or legal-advice system. Production controls outside this repository include lawful basis, consent, retention enforcement, audit operations, incident response, subject-request orchestration, backup erasure, and case approval.

The Layer1, Layer2, and Layer3 names describe the project's conceptual organization. The SQL implementation is Databricks- and Spark-specific.

Source-path notation

Each page lists repository-relative source paths as code, for example models/layer2/int_invoice_resolution.sql. These paths identify implementation evidence; they are not documentation-site routes.