SNS Hybrid Data Foundation - Governed Data Lakehouse on AWS

Every AI programme eventually stalls at the same place: the data. It is spread across file shares, databases and line-of-business systems, quality is unknown, ownership is unclear, and moving all of it to the cloud is neither legally possible nor commercially sensible. The result is copies, exports and shadow datasets that no one governs. This service replaces that with a single governed foundation that spans on-premises and AWS.

SNS builds an open lakehouse on Amazon S3 using the Apache Iceberg table format, with AWS Glue for ingestion and transformation, AWS Lake Formation for fine-grained permissions, and Amazon Athena and Amazon Redshift for query and serving. Governance is implemented through Amazon DataZone for business glossary, lineage and governed access, AWS Glue Data Quality for rules enforced at ingestion, and Amazon Macie for classification of sensitive data. Open table formats keep you free of engine lock-in and let BI, analytics and retrieval-augmented generation consume the same governed data without duplication. Delivery runs in ten to sixteen weeks, phased by data domain, so value appears after the first domain rather than at the end.

The differentiator is the hybrid layer. As an AWS Storage Competency Partner with more than 28 years of datacenter engineering experience, SNS connects existing NetApp, Dell and VMware estates to AWS so that regulated or latency-bound datasets remain on premises while derived and non-sensitive data lands in the lakehouse. This service relates to the following AWS services: Amazon S3 including S3 Tables, AWS Lake Formation, AWS Glue, AWS Glue Data Quality, Amazon Athena, Amazon Redshift, Amazon EMR, Amazon MSK, Amazon Kinesis, AWS Database Migration Service, Amazon FSx for NetApp ONTAP, AWS Storage Gateway, AWS DataSync, AWS Direct Connect, Amazon DataZone, Amazon QuickSight, Amazon Macie and AWS Backup. The foundation is designed to be consumed directly by the SNS Sovereign AI Landing Zone service.