Building ETL Pipelines With Generative AI


October 1st, 2023

51 mins 36 secs

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About this Episode


Artificial intelligence applications require substantial high quality data, which is provided through ETL pipelines. Now that AI has reached the level of sophistication seen in the various generative models it is being used to build new ETL workflows. In this episode Jay Mishra shares his experiences and insights building ETL pipelines with the help of generative AI.


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  • Your host is Tobias Macey and today I'm interviewing Jay Mishra about the applications for generative AI in the ETL process


  • Introduction
  • How did you get involved in the area of data management?
  • What are the different aspects/types of ETL that you are seeing generative AI applied to?
    • What kind of impact are you seeing in terms of time spent/quality of output/etc.?
  • What kinds of projects are most likely to benefit from the application of generative AI?
  • Can you describe what a typical workflow of using AI to build ETL workflows looks like?
    • What are some of the types of errors that you are likely to experience from the AI?
    • Once the pipeline is defined, what does the ongoing maintenance look like?
    • Is the AI required to operate within the pipeline in perpetuity?
  • For individuals/teams/organizations who are experimenting with AI in their data engineering workflows, what are the concerns/questions that they are trying to address?
  • What are the most interesting, innovative, or unexpected ways that you have seen generative AI used in ETL workflows?
  • What are the most interesting, unexpected, or challenging lessons that you have learned while working on ETL and generative AI?
  • When is AI the wrong choice for ETL applications?
  • What are your predictions for future applications of AI in ETL and other data engineering practices?

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Parting Question

  • From your perspective, what is the biggest gap in the tooling or technology for data management today?

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The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

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