Applications and Challenges for Large Language Models: From Data Management Perspective

Meihui Zhang, Zhaoxuan Ji, Zhaojing Luo, Yuncheng Wu, Chengliang Chai

Abstract: Data management is indispensable for informed decision-making in the big data era. In the meantime, Large Language Models (LLMs), equipped with billions of model parameters and trained on extensive data corpora, have recently achieved record-breaking results in various real-world applications, such as machine translation, content generation, information retrieval, etc. The emergent abilities of LLMs, e.g., in-context learning and advanced reasoning ability, have great potential to revolutionize data management. In this paper, we first present some promising categories of data management applications where LLMs can be adapted, including data generation, data transformation, data integration, and data exploration. We then discuss the corresponding challenges for such adaption. Finally, we envision potential solutions to these challenges.