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Data Mesh Implementation Patterns

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 Connect with us: Website: https://databricks.com Facebook:   / databricksinc   Twitter:   / databricks   LinkedIn:   / data.  . Instagram:   / databricksinc