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1、Data Mesh Best PracticesAbout me20+years of data and engineering experienceArchitect,builder,speakerFocused on the maturation,and modernization of dataAWS Data HeroFounder of Data FuturesFather of 4(3 boys,1 girl).always building:welding/fabrication/machining/wiring/engineering/programmingWhy do I c
2、are about Data MeshIm a software engineer first,but my superpower is data engineeringMaturing of data engineering system architecture and cultureData MaturityAdopting Data Mesh principles can actually bring Data Engineering to similar Maturity as other well engineered software products.Event Based M
3、icroservice be better to dataAND data,be betterData MeshComposable data architecture of data products with decentralized ownership and development.https:/ course on data mesh4 principles1.Domain Driven Ownership Organization and Culture -decentralized ownership Federated DevelopmentData Organization
4、 Maturity LevelsCentral-central data team,middle man,a difficult/near impossible jobEmbedded-centrally managed engineers align/embed with product/outcome teamsFederated-central teams develop tools,product/outcome teams execute 2.Data as a ProductApply“Data Product Think”.Data is not an afterthought.
5、Data is not what comes out of the tailpipe.Data is a non-functional/functional requirement for all products REQUIRES long term thinking and organizational alignmentData Product ThinkWhat are my analytic requirements?How will i measure the success of this feature/product?What are the requirements of
6、my data,both within my domain/team,and that of my customers?How can I robustly share my data model as fully as possible?Organizational AlignmentReward system,based on MetricsExisting precedence to leveragetech debtinfrastructuredevex3.Self Service Data PlatformData should be:easy to discover and und