Star Cement Azure to AWS Data Lake Migration

multi · data pipeline diagram.

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About This Architecture

Star Cement's Azure-to-AWS data lake migration architecture consolidates 700 GB of historical data and live transactional sources into a unified AWS S3 data lake with bronze-silver-gold layering. Azure Data Lake, SAP S/4HANA, and RDS databases feed AWS Glue ETL, DMS CDC, and Lambda processors orchestrated by Step Functions, reducing reporting latency from 24 hours to 15-45 minutes. This enterprise platform demonstrates hybrid cloud data integration, change data capture for incremental refresh, and governance through Lake Formation and Glue Data Catalog. Fork this diagram on Diagrams.so to customize source systems, adjust refresh targets, or adapt the migration strategy for your organization. The architecture balances one-time historical migration via DataSync/Snowball with ongoing streaming CDC, enabling real-time analytics on Power BI, Athena, Redshift, and QuickSight.

People also ask

How do you migrate a 700 GB Azure data lake to AWS while maintaining real-time incremental refresh and reducing reporting latency?

This diagram shows a layered approach: AWS DataSync/Snowball handle one-time 700 GB historical migration, while DMS CDC captures incremental changes from SAP S/4HANA and RDS. Glue ETL and Lambda transform data through bronze (raw), silver (processed), and gold (curated) S3 zones, orchestrated by Step Functions. Result: reporting latency drops from 24 hours to 15-45 minutes.

Star Cement Azure to AWS Data Lake Migration

MultiadvancedAWSAzuredata-lakeETLmulti-cloudmigration
Domain: Cloud MultiAudience: Enterprise data architects planning multi-cloud migrations from Azure to AWS data lakes
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Created by

March 25, 2026

Updated

March 25, 2026 at 8:11 AM

Type

data pipeline

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