Data Modernization

Data Modernization

Your data platform is either your competitive advantage — or your biggest constraint.

Data Modernization is the structured process of transforming legacy data platforms into modern, AI-ready architectures. It’s not just a technical upgrade. It’s what makes every future initiative — from advanced analytics to generative AI — possible, reliable, and fast.

What makes our frameworks different

Frameworks & LACE: Integrated Approach

What problems do they solve?

What problems do they solve?

Organizations repeatedly face the same challenges when building data platforms — ensuring data quality, lineage, governance, orchestration, and cost control. Solving these from scratch in every project leads to duplication, inconsistency, and high delivery risk.
What are the frameworks?

What are the frameworks?

Data frameworks address this by providing pre-built, production-ready components that embed best practices from day one. Instead of building foundations manually, teams start from a proven baseline — accelerating delivery, standardising operations, and reducing technical debt.
LACE role in Data Modernization

LACE role in Data Modernization

LACE’s role is to tackle the hardest part of modernization — understanding and transforming legacy systems. Using agentic AI, LACE extracts business logic, maps dependencies, designs target models, and generates pipelines. Fully integrated with the frameworks, it ensures that everything produced is governed, consistent, and production-ready.
Customer value

Customer value

Customer value is immediate: faster time-to-value, lower risk, and scalable, maintainable data platforms.
"Data Modernization is not a migration project. It's the decision to stop paying the hidden tax of your past and start building the infrastructure your business actually needs to compete in an AI-driven world. Our frameworks exist to make that journey faster, safer, and genuinely measurable."
Luis Marques Luis Marques Global Head of Data
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