### Database Schema:
CREATE TABLE violations (
	business_id	INTEGER	NOT NULL,
	date	DATE	NOT NULL,
	violation_type_id	TEXT	NOT NULL,
	risk_category	TEXT	NOT NULL,
	description	TEXT	NOT NULL,
	foreign key (business_id) references businesses (business_id)
);

CREATE TABLE inspections (
	business_id	INTEGER	NOT NULL,
	score	INTEGER	NULL	DEFAULT NULL,
	date	DATE	NOT NULL,
	type	TEXT	NOT NULL,
	foreign key (business_id) references businesses (business_id)
);

CREATE TABLE businesses (
	business_id	INTEGER	NOT NULL	PRIMARY KEY,
	name	TEXT	NOT NULL,
	address	TEXT	NULL	DEFAULT NULL,
	city	TEXT	NULL	DEFAULT NULL,
	postal_code	TEXT	NULL	DEFAULT NULL,
	latitude	REAL	NULL	DEFAULT NULL,
	longitude	REAL	NULL	DEFAULT NULL,
	phone_number	INTEGER	NULL	DEFAULT NULL,
	tax_code	TEXT	NULL	DEFAULT NULL,
	business_certificate	INTEGER	NOT NULL,
	application_date	DATE	NULL	DEFAULT NULL,
	owner_name	TEXT	NOT NULL,
	owner_address	TEXT	NULL	DEFAULT NULL,
	owner_city	TEXT	NULL	DEFAULT NULL,
	owner_state	TEXT	NULL	DEFAULT NULL,
	owner_zip	TEXT	NULL	DEFAULT NULL
);

### User's Query:
In businesses with a score lower than 95 and located around the postal code of 94110, what is the percentage of businesses with a risk category of low risk?

### Extra Knowledge:
DIVIDE(COUNT(business_id where risk_category = 'Low Risk', score < 95 and postal_code = 94110), COUNT(business_id where score < 95 and postal_code = 94110)) as percentage;
SELECT CAST(SUM(CASE WHEN T1.risk_category = 'Low Risk' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.risk_category) FROM violations AS T1 INNER JOIN inspections AS T2 ON T1.business_id = T2.business_id INNER JOIN businesses AS T3 ON T2.business_id = T3.business_id WHERE T2.score < 95 AND T3.postal_code = 94110