Data Pipeline

Data pipelines are automated systems for processing and transforming data, aiming to efficiently move data from raw sources to usable formats for analysis or machine learning. Current research emphasizes improving pipeline efficiency and reproducibility, often employing techniques like Lambda architectures for real-time and batch processing, and leveraging large language models for semantic querying and automated data quality validation. These advancements are crucial for various applications, including large language model training, scientific data analysis, and improving the reliability and scalability of machine learning workflows in diverse fields like healthcare and precision agriculture.