Data Engineering Podcast cover image

Data Engineering Podcast

The Future of Data Engineering: AI, LLMs, and Automation

Feb 26, 2025
Gleb Mezhanskiy, CEO and co-founder of Datafold, shares insights from his journey in data engineering and the integration of AI. He discusses how large language models can streamline code writing, improve data accessibility, and facilitate testing and code reviews. Mezhanskiy emphasizes the challenges at the intersection of AI and data workflows, advocating for continuous adaptation. With practical applications like text-to-SQL and enhanced data observability, he paints an optimistic picture for the future of data engineering.
59:39

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Podcast summary created with Snipd AI

Quick takeaways

  • AI technology can significantly expedite data migrations, making them up to ten times faster through automation and efficient code translation.
  • Distinct operational workflows between data engineering and software engineering necessitate specialized tools to address the unique complexities of managing data.

Deep dives

AI-Powered Data Migrations

AI technology has the potential to revolutionize data migrations, which are typically prolonged and resource-intensive endeavors. Automation tools, such as Datafold's AI-powered migration agent, can drastically reduce migration timelines by translating code and validating data automatically. This efficiency allows companies to complete migrations up to ten times faster than traditional methods, alleviating stress and resource drain. Additionally, with a written guarantee on timelines, businesses can confidently plan their operations around faster data migrations.

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