SQL and Python Data Cleaning | Dataford Interview Questions

Tell me about your experience using SQL commands and Python for data cleaning.

For the SQL portion, write a PostgreSQL query that standardizes names, emails, and phone numbers, removes invalid or unsupported email records, handles missing phone values, and keeps the most recently updated record for duplicate emails.

Output

One row per accepted email record with record_id, cleaned_name, cleaned_email, cleaned_phone, and updated_at.
Exclude invalid, missing, duplicate older, and unsupported-domain email records.
Sort by cleaned_email, then record_id.

Schema

raw_customer_records

Column	Type	Description
record_idPK	INT	Unique raw record identifier
full_name	VARCHAR(150)	Unstandardized person name
email	VARCHAR(255)	Raw email address
phone	VARCHAR(40)	Raw phone number
updated_at	TIMESTAMP	Timestamp of the source record update

email_domain_rules

Column	Type	Description
domainPK	VARCHAR(120)	Supported lowercase email domain
domain_label	VARCHAR(120)	Readable domain description

Your question is SQL and Python Data Cleaning. Start with the requirements and the two tables in the Question tab.

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Problem