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SQL Join and Record Resolution
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SQL Join and Record Resolution

HardSQL · PostgreSQL

Problem

Write a SQL query to join multiple fragmented datasets and resolve conflicting customer records based on incomplete demographic data.

Use the provided customer registry, fragmented profile records, and orders. Match profiles to registry customers using available demographic fields, retain only credible matches, select the strongest profile for each customer, and include unmatched registry customers.

Output

  1. One row per registry customer.
  2. Include canonical customer fields, the selected fragment ID and match score, matched fragment count, order count, total spend, and matched source names.
  3. Sort by customer_id ascending. Return zero values for customers without orders.

Schema

customer_registry
ColumnTypeDescription
customer_idPKINTCanonical customer identifier
canonical_nameVARCHAR(100)Canonical customer name
canonical_emailVARCHAR(150)Canonical email address
birth_dateDATECanonical date of birth
postal_codeVARCHAR(10)Canonical postal code
source_profiles
ColumnTypeDescription
fragment_idPKINTFragmented profile identifier
source_nameVARCHAR(40)Originating source system
full_nameVARCHAR(100)Name reported by the source
emailVARCHAR(150)Email reported by the source
birth_dateDATEBirth date reported by the source
postal_codeVARCHAR(10)Postal code reported by the source
source_priorityINTPriority used to break equivalent matches
source_orders
ColumnTypeDescription
order_idPKINTOrder identifier
fragment_idINTProfile fragment associated with the order
amountNUMERIC(12,2)Order amount
Tablescustomer_registrysource_profilessource_orders
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CodePostgreSQL
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