Abstract
In data stores with large tables running into a very large number of rows, it is difficult and computationally intensive to find the specific information required for a particular task. Summary tables or rollups are manually created in advance by condensing the data from a parent table. This disclosure describes the use of generative artificial intelligence (genAI) techniques to automatically generate suggestions for summary tables and code to create such tables. The genAI model is provided with an appropriate prompt and relevant information such as past summary tables, popular data models, SQL queries to the parent table, etc. and generates suggestions for summary tables. The use of a genAI model can support the automation of workflows within any data warehouse infrastructure. It can reduce the need for human data engineers to build data models from scratch and write the code to construct the corresponding summary tables.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Wolf, Lois, "Creating Summary Tables for Large Stores Using Generative Artificial Intelligence", Technical Disclosure Commons, (June 10, 2025)
https://www.tdcommons.org/dpubs_series/8219