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Cloud Data Warehouse Modernization and Analytics Platform Development
  1. case
  2. Cloud Data Warehouse Modernization and Analytics Platform Development

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Cloud Data Warehouse Modernization and Analytics Platform Development

future-processing.com
Information technology
Business services
Consulting

Legacy Infrastructure Limitations

The client's existing on-premises data warehouse architecture hindered scalability, data accessibility, and real-time decision-making capabilities. Legacy systems (MS SQL) created bottlenecks in data ingestion, increased operational complexity, and failed to meet modern security and compliance standards required for global operations.

About the Client

A century-old global leader in technology consulting and business innovation, specializing in data-driven solutions and digital transformation across multiple industries.

Modernization Goals

  • Migrate data warehouse infrastructure from on-premises to AWS Cloud
  • Implement secure, scalable data ingestion pipelines from hybrid sources
  • Enhance business intelligence capabilities through cloud-native analytics
  • Improve data accessibility for global teams while maintaining compliance
  • Reduce total cost of ownership (TCO) through cloud optimization

Core System Capabilities

  • AWS Redshift-based data warehouse architecture
  • Data ingestion from AWS Data Lake and on-premises sources
  • Automated ETL/ELT processes with error handling
  • Migration from MS SQL to PostgreSQL on AWS RDS
  • PowerBI integration for real-time dashboards
  • Role-based access control (RBAC) for data security

Technology Stack

AWS Redshift
PostgreSQL
AWS Data Lake
PowerBI
Redshift Spectrum

System Integrations

  • Legacy on-premises MS SQL databases
  • AWS CloudTrail for audit logging
  • ServiceNow for service desk operations

Operational Requirements

  • 99.95% system availability
  • Data encryption at rest/in transit
  • Auto-scaling capabilities
  • Disaster recovery with RTO <2 hours
  • GDPR/HIPAA compliance

Business Value

Enables data-driven decision-making through real-time analytics, reduces infrastructure maintenance costs by 40%, improves cross-regional collaboration, and achieves 3x increase in customer satisfaction metrics (NPS). The cloud architecture supports 10x data volume growth while maintaining sub-second query performance.

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