Mastering text-to-SQL: how to generate accurate queries

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Mastering text-to-SQL: how to generate accurate queries

Hosted by George Xing

Wed, Apr 16, 2025

4:00 PM UTC (30 minutes)

Virtual (Zoom)

Free to join

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229 students

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AI-Powered Product Analytics

George Xing

View syllabus

Wed, Apr 16, 2025

4:00 PM UTC (30 minutes)

Virtual (Zoom)

Free to join

229 students

Invite your network

Go deeper with a course

AI-Powered Product Analytics

George Xing

View syllabus

What you'll learn

Business-specific context

Provide LLMs with relevant context, without requiring engineers or a complex system.

Testing mechanism

Automate query validations to checks to reduce hallucinations.

Sample prompts

Get access to prompts used to generate queries on real datasets.

Why this topic matters

Text-to-SQL has enormous potential to unlock the value of data for business people. However, LLMs are often missing critical context about your business and data, making it easy for AI tools to hallucinate and generate poor results. In this lightning lesson, I'll share simple ways you can generate more accurate SQL queries immediately.

You'll learn from

George Xing

Product Lead for Data Products at Stripe, former Head of Analytics at Lyft.

George has spent more than a decade working in data as a product builder, analytics leader, founder, and startup advisor.

He was head of analytics at Lyft from 2014-2020 and spearheaded data-driven decision-making at the company through a period of 100x growth.

After Lyft, George co-founded Supaglue, a data integrations company that raised funding from Benchmark Capital and exited to Stripe.

Currently, George is a product manager at Stripe leading the development of analytics and data products. In his free time, he enjoys making coffee with his v60 and going on long runs.

Previously at