SQL Contact Cleaning | Synthetic Demo

SQL contact cleaning and validation — synthetic demonstration.

A small business receives a contact export with inconsistent spacing, duplicate customer IDs, missing emails, and an address that needs review. This AI-assisted sample uses eight fictional records and contains no client or proprietary data.

A SQL view trims names and IDs, normalizes email case, and assigns review statuses. A window count identifies duplicate customer IDs. CASE rules keep missing values and basic email-format exceptions visible. All original source rows are preserved.

The demonstration flags four rows: two duplicate-ID rows, one missing email, and one format exception. Four rows pass these limited screening rules. Passing does not prove that an email is deliverable.

Deliverables include a runnable SQL script and CSV review output. The query was executed in SQLite. Expected counts and normalization were checked. A temporary source change updated its review status correctly, then was restored. This syntax was tested in SQLite, not Microsoft Access or SQL Server.

This illustrates a focused freelance assignment: clean a contact export, document the review rules, and deliver traceable exceptions for the business owner to resolve.