Quantifying the Business Impact of Starburst’s AI-Ready Data Platform

Independently Validated by Enterprise Strategy Group (Omdia)

This Economic Validation was conducted by Enterprise Strategy Group (ESG), now Omdia, a leading independent technology research and validation firm. 

The study is based on in-depth customer interviews and quantitative modeling using conservative economic assumptions. It evaluates the real-world business impact of the Starburst Data Platform for Apps and AI compared to traditional, fragmented data architectures.

Why Traditional Data Platforms Hold Enterprise Back

Most organizations collect massive volumes of data yet struggle to use it effectively for AI, analytics, and innovation. ESG’s research highlights persistent challenges:

• Data fragmented across clouds, on-premises, and hybrid environments
• Rising costs driven by duplication, ETL pipelines, and infrastructure sprawl
• Slow onboarding of new data sources that delay insights
• Governance complexity that limits agility and AI readiness

The outcome is underutilized data, slower innovation, and rising operational costs.

What Organizations Achieved with Starburst

ESG’s three-year modeled scenario shows how organizations using the Starburst Data Platform achieve measurable improvements across three core areas: 

Unified, On-Demand Access to Enterprise Data

A single access layer across enterprise data sources that eliminates forced migration and lock-in, enabling faster onboarding of new data and broader analytics adoption

Lower Costs and Predictable Performance at Scale

Improved price-performance for queries, reduced cloud and infrastructure spend, and significantly lower operational overhead compared to legacy approaches.

Faster Innovation and AI-Ready Data Operations

Faster experimentation, quicker AI development cycles, and greater flexibility to adopt new technologies without re-architecting the data stack

ESG’s modeled results include:

• 45% lower total cost of ownership compared to baseline data architectures
• 414% three-year ROI under conservative assumptions
• Material reductions in operational, development, processing, and storage costs
• Reduced downtime risk for analytics and revenue-generating services
• Revenue upside enabled by faster product innovation and improved data accessibility

The full methodology, assumptions, and breakdown are detailed in the report.

Who This Report Is For

• CIOs, CDOs, and CTOs evaluating data platform investments
• Finance and procurement leaders assessing ROI and cost optimization
• Data and analytics leaders modernizing for AI and advanced analytics
• Product and application teams building data-driven experiences

If you’re being asked to justify data infrastructure investments with defensible, board-ready numbers, this report can help.

Inside the Report, You’ll Find:

• ESG’s three-year economic model and assumptions
• Breakdown of cost savings by category
• Analysis of avoided risk and revenue impact
• Real customer perspectives on operational efficiency and innovation
• How unified data access changes the economics of AI readiness