Semantic Layer is about decomposing views into dimensions and aggregates, then letting downstream apps/users compose their own views on top without having to redefine/re-calculate business level metrics.
This makes data analyis more flexible than sql views which are hardcoded on particular groupings.
It's a lot more. A SQL VIEW is just a saved query, where a semantic layer defines the shared meaning of the data, and helps enforce consistent metrics, joins, and logic across tools. You'd be surprised at how many ways "active customer" can be represented as SQL.
create view active_cx as select * from customer join audit_events using(...) join ... where -- active condition
-- use active_cx wherever
select ... from orders join active_cx using(...) where ts > start_of_month() group by active_cx.id
