Handling 30% Missing Critical Data | Dataford Interview Questions

How would you handle a dataset where 30% of the entries are missing critical information at American Credit Acceptance?

For this exercise, evaluate completeness for each loan application source. Treat NULL or blank employment status, and NULL values in income, requested amount, or credit score as missing critical information.

Output

One row per application source, including applications with no matching source.
Columns: source_name, total_entries, missing_entries, and missing_percentage.
Sort by missing percentage descending, then source name ascending.

Schema

loan_applications

Column	Type	Description
application_idPK	INT	Unique loan application identifier
source_id	INT	Identifier of the application submission source
annual_income	DECIMAL(12,2)	Applicant annual income
employment_status	VARCHAR(40)	Applicant employment status
requested_amount	DECIMAL(12,2)	Requested loan amount
credit_score	INT	Applicant credit score

application_sources

Column	Type	Description
source_idPK	INT	Unique application source identifier
source_name	VARCHAR(60)	Name of the application submission source

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Problem