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hey everyone uh Jerry here from llama index and in this video weamp;#39;ll teach you how to build query pipelines over structured or tabular data so when we try to build for the use case of question answering over tabular data the tabular QA stack looks quite different from the traditional rag stack which is primarily over unstructured data rag typically looks like you have a input query and then you do topk retrieval of text chunks from a vector database you take those text Trunks and you stuff it into the prompt to do response synthesis now thereamp;#39;s been a few Stacks that have emerged for quaring over tabular data and they typically take the form of either pandas data frames or as a SQL database or a SQL database collection and so in those settings letamp;#39;s say for a pandas data frame um we call this text a pandas but typically you know you would take in an input query convert this to a set of pandas operations through an llm prompt so actually ask the LM to generate a s