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Sponsored by NextData, Zhamak's company that is helping ease data product creation.
For more great content from Zhamak, check out her book on data mesh, a book she collaborated on, her LinkedIn, and her Twitter.
Key Takeaways:
- We need to make the data product the first class primitive of information sharing - make them the basic building block of how we create our internal data/AI ecosystem. (repeat from ZC20)
- "Tools reshape behavior" - if we want developers to change their relationship to data, we need to give them the capability to do so easily. Or even if not easily, at least not arduously :)
- The industry sees the value of data mesh but we need to find much lower effort ways to create sustainable, large-scale change. We all need to be finding catalysts.
- There is no reason to try to reinvent a lot of the technology in data at the physical layer. Lake storage, streaming technologies, ML libraries _at the physical layer_ are great. But we need new ways of accessing and leveraging them to make it far easier to create and manage data products.
- While everyone seems to be talking data products, there seems to be so many different definitions. This has led to a weaker market pull on vendors to improve their tooling to make data mesh more easily possible.
Semantic Diffusion article Zhamak mentioned: https://www.martinfowler.com/bliki/SemanticDiffusion.html
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