Exploring RAG Fundamentals

Generative AI is all the rage right now. But, just because a GenAI initiative sounds exciting doesn’t necessarily mean it’s going to drive business value.

In order for GenAI to tangibly impact a business’ bottom line, it needs to leverage curated data for a clear business use case. But how?

Teams are turning to an emerging, but already essential, framework to differentiate their AI for business value: Retrieval augmented generation (RAG). In this eBook, we’ll dive into everything a data engineer in the age of AI needs to know about RAG: what it is, how it works, and how to get started.

You’ll learn:

RAG fundamentals, including the core architecture, structure, and operational data flow
Core RAG tools, including vector databases and data observability
Fine-tuning basics, and how it can be used with RAG
Real-life GenAI use cases from teams like Preset and Credit Karma
How to operationalize data reliability when developing RAG applications

Download Understanding the Basics: RAG for AI now!