Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Integrating Large Language Models into Data Engineering Workflows
0
Zitationen
1
Autoren
2025
Jahr
Abstract
Large Language Models (LLMs) are transforming data engineering by automating complex tasks, enhancing accessibility, and improving efficiency. This paper explores the integration of LLMs into data engineering workflows, highlighting specific use cases such as ETL automation, query optimization, compliance reporting, and conversational interfaces. Through real world examples and scholarly insights, we demonstrate how LLMs are reshaping the role of data engineers and enabling more intelligent, scalable systems.
Ähnliche Arbeiten
UCSF Chimera—A visualization system for exploratory research and analysis
2004 · 47.551 Zit.
SciPy 1.0: fundamental algorithms for scientific computing in Python
2020 · 37.096 Zit.
Clustal W and Clustal X version 2.0
2007 · 29.008 Zit.
The REDCap consortium: Building an international community of software platform partners
2019 · 23.552 Zit.
Array programming with NumPy
2020 · 21.680 Zit.