Research on data development technology in artificial intelligence and big data

This study discusses the key role of data development technology in the application of artificial intelligence and big data, especially in improving the efficiency of data processing, optimizing model training and enhancing system performance. Firstly, an efficient data processing architecture is designed, including data hierarchical storage and parallel processing mechanism, which effectively improves the speed of data retrieval and processing. Dynamic feature selection and generation techniques are also introduced to dynamically adjust and create features through machine learning models to meet the needs of model training. This paper experimentally evaluates the performance of different data development techniques in terms of processing speed, accuracy, and resource consumption. Results show that processing efficiency and model performance can be significantly improved by using Spark and adaptive learning algorithms.