Part 5/9:
The session also delved into the transformative potential of generative AI, specifically models like ChatGPT. While the full impact on data engineering remains to be seen, the speaker noted ongoing efforts within his organization to develop in-house generative AI models tailored to industry-specific needs, such as supporting data quality for pharmaceutical companies.
Although the integration of AI into data engineering workflows is still unfolding, there is optimism about its future role in automating and enhancing data processes, reducing manual efforts, and generating new insights that were previously difficult to access.