Abstract
Cloud database customers can inspect the data they store across multiple databases (potentially spanning across multiple database products) and find details such as schema and nature of stored data from individual database products. This requires technical knowledge of database querying and programming, which complicates business analytics and planning. This disclosure describes techniques to leverage data cataloging services and large language model (LLM) tools to analyze database schema information and to generate contextual information about the structures of the databases owned by a customer. By combining the power of an LLM chatbot with the schema gathering abilities of data cataloging services, details of the database structures are abstracted away, such that non-technical customers can query and find statistical relationships of interest within their data without writing SQL code. The abstraction of the database and the doing away of manual programming enables customers to focus on their businesses instead of dealing with the intricacies of database systems.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Aksakal, Ahmet Salih, "Large Language Model (LLM) Business Helper for Cloud Databases", Technical Disclosure Commons, (July 03, 2024)
https://www.tdcommons.org/dpubs_series/7158