Query & Theory

Sending regular reports out via email is a great way to disseminate insights and SQL and Python are great for advanced analysis and conditional reporting. In this how-to tutorial we show you how to leverage Fabi.ai to send your first email in 5 minutes.

AI is ushering a new era of augmented analytics. Data leaders and executives across industries need to consider how they're using augmented analytics to make better, faster, real-time decisions.

Many SaaS providers have, or are considering, deploying private LLM models to address privacy concerns. However, these come at a cost. In this article, we talk about our experience deploying and integrating a private LLM for our most privacy-sensitive customers.

Enterprise analytics consolidates data from across your organization to reveal strategic insights that drive growth. Learn more about how to get started and the role of AI.

Finding and sharing true insights is hard: legacy BI was not designed for deep exploration while data teams struggle to hire a balance of technically proficient and business-savvy individuals. New technology, platforms and AI are changing the game.

Failing to understanding confounding variables can lead to incorrect conclusions (and decisions) about cause and effect. In this post we dive into examples and how to handle confounding variables.

A great SQL IDE is a must-have for data practitioners of all levels. In this post, we talk about all the best IDEs, their pros and cons and which to consider based on your needs.

A technical deep-dive into building Fabi.ai's Analyst Agent, from AI agent architecture decisions to implementing an enterprise-grade agent framework.

BI and data analytics are close cousins but do have their differences. In this article we explore their definitions and the pros and cons of each to help guide in your decision.

Thanks to Analyst Agent, data teams can quickly create, configure and deploy AI agents to let business teams explore data on their own.

Data cleaning is the first step of making good use of any data. However, it has its challenges. In this post we explore the challenges and best alternatives.

In this article we explore the different reasons to consider Python for code generation and the top 5 tools in 2025 depending on your use case.

3 quick ways to run a Python script in just a few minutes.