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Data Mesh: Decentralizing and Unifying Data Resources

Last updated Feb 9, 2024

In the evolving landscape of data management, Data Meshes emerge as a crucial concept, trying to bridge the gaps between isolated data teams. Their core value lies in fostering a shared understanding and usage of data across diverse teams within an organization.

By effectively interlinking platforms, Data Meshes facilitate seamless data transfer, enhancing the organizational workflow. This approach combats the typical disconnect in data handling, offering a solution that balances decentralized resources with a unifying common infrastructure. It empowers domain experts, granting them ownership and control over their data domains.

For deeper insights, consider exploring the foundational paper on this topic, the succinct explanation in What the Heck is a Data Mesh?! or the visually engaging Data Mesh Architecture. Practical applications and perspectives are well-articulated in Data Mesh in Practice.


A nice of the problem of a central data platform team | Share on LinkedIn

# Fleeting Thoughts

From the Netflix Technology blog:

I agree that naming is confusing, but it’s just an unfortunate timing: the development of “Data Mesh” (DM) platform at Netflix started around the same time, Zhamak Dehghani an first defined the term in the “Beyond the lake” talk in 2018. As we state, “we define Data Mesh as a general purpose data movement and processing platform for moving data between Netflix systems at scale”, nothing more, nothing less. RW Data Mesh — A Data Movement and Processing Platform @ Netflix by Netflix Technology Blog Netflix TechBlog

From Reddit - Dive into anything:

More on Why data pipeline should not be outside of data product.

# Demystifying Data Mesh

# Additional Resources


References: RW How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh Reverse ETL
Last Modified: 2021-10-28
Created 2021-10-28