利用湖畔建筑打破数据孤岛.pdf

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利用湖畔建筑打破数据孤岛.pdf

1、 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.A N T 3 3 7Breaking data silos with the Lakehouse architectureVincent Gromakowski(He/Him)Principal Analytics SASrividya Parthasarathy(She/Her)Senior Big Data Archite

2、ct,AWS Lake Formation 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Agenda1.Challenges with Data silos 2.What is Lakehouse architecture3.Lakehouse Interoperability patterns4.Recap and call to action 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Workload spec

3、ific stores have created data silos Lack interoperabilityIntegration crisis with no standard integration protocol Inconsistent governanceGovernance policies and enforcement varies based on where the data is storedComplex architectureMultiple copies of data and governance to support different workloa

4、dsLonger time to valueLonger time to value to support new analytic and AI/ML use cases 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Lakehouse Architecture of Amazon SageMaker S I M P L I F Y A N A L Y T I C S A N D A I W I T H A U N I F I E D,O P E N,A N D S E C U R E D A T A L

5、 A K E H O U S ELakehouse UnifiedAchieve unified access to all your dataOpenUse your preferred analytics and ML engines with an open interfaces SecureSecure your data with consistent access controls 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.O P E N A C C E S S T O D A T AApa

6、che Iceberg compatibilityApache Iceberg REST Catalog APIsIceberg compatibility beyond your data lakeAWS native and 3rd party compatibleSageMaker Unified StudioAWS Analytics Services3rd Party ApplicationsApache Iceberg APIsUnified technical metadata&access controlFederated CatalogsManaged Catalogs Am

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