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The field of data engineering is constantly evolving, with new trends such as seamless data sharing, data lake house modeling, and low code data integration emerging. These changes are driven by advancements in AI, ML, cloud computing, and big data technologies. Additionally, large language models are becoming more prevalent, acting as co-pilots for data scientists and engineers and improving productivity. Another trend to watch is retrieval-augmented generation, which incorporates external data sources to improve the accuracy of generative AI models.