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Follow the Aurelia customer data
Trace the sample records, catalog relationships, and data defects before reviewing quality or duplicates.
Installed tables and records
GET /api/entities/sample-customer-entity
Records in sample_customer | 378 — 294 from the CRM, 84 from billing |
| Duplicate groups | 350 across the customer’s four index mappings |
| Entity type | DUPLICATES, status READY |
The second entity, sample-lead-entity, has 108 sales leads, 15 duplicate
groups, and its own cleaning pipeline and quality measurement.
The installation also creates three lookup tables:
| Table | Rows | What it is |
|---|---|---|
sample_customer | 378 | The unified customer master. Keeps history and audit |
sample_supply_point | 1200 | Supply points (CUPS), the master a customer’s meter points at |
sample_province | 20 | Provinces. A master table that itself references another master table |
sample_region | 17 | Autonomous communities |
Lookup relationships
sample_province carries a FOREIGN_ID column resolving against
sample_region.regionCode, and sample_customer carries two of them —
province against sample_province.province, and supplyPoint against
sample_supply_point.cups. These relationships let you inspect a lookup from a customer to a province
and from that province to a region.
A record form presents lookup catalogs of up to 500 values as a select control. Larger catalogs use a search input. The 1,200 supply-point records let you test the search behavior alongside the smaller province and region catalogs.
Sample quality issues
The CRM and billing source files include differences in formatting, incomplete emails, and missing identifiers or phone numbers. The installed cleaning pipeline normalizes values it can repair before storage. Download the sample files from Administration → Settings → Sample projects → Download files to compare source and stored forms.
Three records for Ana García Muñoz
| Source file | Reference | Full name | Tax ID | Phone | |
|---|---|---|---|---|---|
| CRM | CRM-0001 | Ana García Muñoz | 12345678Z | ana.garcia@example.com | 611000000 |
| CRM | CRM-DUP-0001 | ANA Garcaí Muñoz | 12345678Z | Ana.Garcia@Example.com | +34 611 00 00 00 |
| BILLING | BILL-0001 | Ana Garcia Munoz | (empty) | ana.garcia@ | (none) |
The second CRM source row represents Ana with differences in case, spacing,
spelling, phone formatting, and street abbreviation. After cleaning, the two
CRM phones are both stored as +34611000000; the surname typo remains.
The billing record lacks a tax identifier and phone and has an incomplete email. The name-and-postcode
mapping can still group it for comparison.
Two customers named Javier Torres Melgar
| Tax ID | Street | Postcode |
|---|---|---|
31415926R | Calle Zamora 14 | 37001 |
27182818W | Calle Zamora 16 | 37001 |
These records represent different people with the same name and postcode. The name-and-postcode index groups them as candidates. Their tax identifiers differ, and the classifier gives that field a weight of 3.0.
Inspect the comparison before making a decision. Candidate membership alone does not establish that the records describe the same customer.
Continue with Read sample quality.