Consolidating Fragmented Cloud and On-Prem Data Platforms
Rationalizing Hybrid Data Environments to Reduce Complexity
- Service: Data Modernization & Cloud Platforms
- Industry: Data platforms and cloud
- Chicago, IL, USA
Executive Summary
Organizations that grow through acquisitions often inherit fragmented data platforms across cloud and on-premise environments. This success story showcases how Sloancode helped a mid-market enterprise headquartered in Chicago rationalize a hybrid data environment into a simplified, cost-effective platform.
Client Overview
Our client, a mid-market enterprise operating across multiple business units, faced significant challenges:
- Multiple cloud platforms and on-prem databases
- Duplicate reporting tools and data pipelines
- Escalating cloud and infrastructure costs
The Challenges
- Lack of visibility into total data platform costs
- Inconsistent data definitions across business units
- Operational overhead maintaining redundant platforms
Implementation Process
Planning
Mapped existing platforms, usage patterns, and cost drivers to identify consolidation opportunities.
Execution
Designed a rationalized target architecture consolidating data platforms and pipelines.
Testing
Validated data consistency and performance across consolidated workloads.
Deployment
Executed phased decommissioning of redundant systems while migrating workloads.
The Solution Provided
- Platform Rationalization:Reduced redundant cloud and on-prem systems
- Unified Data Architecture:Standardized pipelines and data models
- Cost Optimization Controls:Improved visibility and governance over usage
Technologies, Methodologies, or Strategies
- Hybrid cloud architecture design
- Data platform cost analysis and optimization
- SQL and Python-based integration pipelines
- Governance and access controls
Explanation of Technologies and Strategies
We applied rationalization-first modernization to reduce complexity before scaling. By consolidating platforms and standardizing architectures, the organization reduced cost and improved maintainability.
Technology Stack
Results Achieved
- 35% reduction in total data platform costs
- Simplified architecture with fewer failure points
- Improved reporting consistency across business units
Team Members and Skillsets
- 1 Data Platform Lead (Architecture and rationalization)
- 2 Data Engineers (Integration and migration)
- 1 Cloud Cost Analyst (Optimization and governance)
- 1 BI Specialist (Reporting validation)
Ready to build a trusted analytics foundation?
“Not sure where to start?
Run our free Enterprise Data, AI & Transformation Readiness Diagnostic to benchmark your organization and uncover the capabilities needed to succeed.”