In this playbook, we'll build a funnel optimization agent that analyzes GA4 ecommerce data with BigQuery SQL, generates recommendations for both product strategy and funnel improvements, and creates an executive summary with prioritized action items to boost conversion rates and increase revenue.
This playbook walks you through building a cost-aware SQL agent that delivers actionable insights from BigQuery. The agent helps data teams democratize access to analytics and avoid unexpected costs through validation and a built-in protection mechanism.
This playbook walks you through building an ecommerce product analytics agent using BigQuery and LangGraph. The agent helps identify opportunities to increase average order value through product combinations, category analysis, and bundle recommendations.
In this tutorial, I will teach you LangChain as efficiently as possible by breaking down the framework into seven key components you need to understand to start developing more advanced LLM applications.
This tutorial will explore building dashboards using Large Language Models (LLMs) and LangChain. We will use LangChain chains to extract insights from BigQuery by first generating SQL and then pushing the generated SQL to BigQuery as views, forming the basis for interactive dashboards.
This guide helps data analysts, data scientists, and developers leverage LLMs for generating SQL queries from natural language questions, making complex data wrangling in BigQuery and other SQL databases more accessible and intuitive.
In this tutorial, we'll operationalize Shopify data in Google BigQuery. By leveraging BigQuery, we'll be able to do reporting, support machine learning, and build the foundation for generating insights with Large Language Models (LLMs).
In this tutorial, we'll extract Shopify data efficiently and lay the groundwork for generating insights via LLM-based interfaces.
