From the course: Advanced RAG Applications with Vector Databases

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From the course: Advanced RAG Applications with Vector Databases

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- [Instructor] Metadata is the final piece of what makes vector databases useful. Without storing metadata, we would just be comparing a bunch of numbers. The term metadata encompasses all of the data that gets stored with your vector embeddings. When it comes to retrieval, augmented generation, we definitely need to store the actual text that the vector embedding was generated from, and we can also store many other types of metadata. So what is metadata? Other than the text itself? There are many different types of metadata. You can think of metadata in many different ways. It's the data that isn't the embeddings that you store in your vector database. A lot of this data falls into the category of data that gets stored in traditional databases, and we'll cover more examples later in this video. You also need to remember that metadata is critical for RAG. It's not just critical for performing basic RAG by providing the text and unvectorized data, but also critical for advanced usage…

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