I've had similar thoughts to the title, but my ideas were more around improving the ease of use/writing. 1. A cleaner universal more natural syntax for analyti

I've had similar thoughts to the title, but my ideas were more around improving the ease of use/writing. 1. A cleaner universal more natural syntax for analytics: I love writing python as it is to me such a cleaner syntax than C or Java. We could do the same for SQL and make something that feels more natural. Turning a common query like > SELECT count(*), TO_CHAR(created_at, 'YYYY-MM-DD') FROM Accounts GROUP BY TO_CHAR(created_at, 'YYYY-MM-DD') ORDER BY TO_CHAR(created_at, 'YYYY-MM-DD'); into something much more natural like > count by Day(Accounts.created_at) 2. A Visual SQL: for analytics it's so much faster to query and explore visually. Building queries visually means you don't make common typo or syntax or structure errors, joins happen smoothly, you can browse the data as you build, you don't need to google for syntax (what's that date function again?), and it works across dialects and databases. We've built and launched this a few months ago at Chartio https://chartio.com/blog/why-we-made-sql-visual-and-how-we-finally-did-it/ https://chartio.com/blog/why-we-made-sql-visual-and-how-we-f...