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Data Mesh Implementation Patterns 

Databricks
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Data mesh has caught the attention of the practitioners with its promise of increased speed to insights and lower data management costs. There is sufficient literature available on “WHAT” of data mesh, but not enough design patterns on “HOW” of data mesh
The presentation will focus on implementation patterns of various data products based on nature of data sources, historical data needs, serving application, consumption requirements. Besides the implementation patterns at execution time, the presentation will also delve into access and search patterns
The implementation patterns are built with a focus on Domain Data as first-class concern as opposed to Data Pipeline as first-class concern, with the following core tenants being embedded as part of all the patterns:
Serving instead of Ingesting
Discovering and using instead of extracting and loading
Publishing events as streams instead of data flowing around via pipelines
Ecosystem of data products instead of centralized data platform
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18 июл 2022

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Комментарии : 5   
@roshanibhatt
@roshanibhatt Год назад
Great presentation & very relevant topic in today's marketplace!
@Engrbrain
@Engrbrain Год назад
Poor presentation really. It is highly conceptual and does not answer the underlying architecture questions about implementing a data mesh
@jackfruit22
@jackfruit22 Год назад
poor, sorry. clarity isn't there.
@okachovik
@okachovik Год назад
Poor , doesn’t explain the technical implementation properly.
@niting123
@niting123 4 месяца назад
poor presentation
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