Making Legacy Data AI-Ready: A Conversation Between AstraZeneca and EPAM
Organizations across industries hold decades of legacy, unstructured, and highly specialized data. This information is often tied to specific domains like scientific research. Traditional processes can’t keep up with the scale and complexity of these massive enterprise datasets.
Advances in large language models (LLMs) and agentic AI now make it possible to convert these assets into structured, AI-ready datasets. This transformation fuels analytics, automation, and innovation at scale.
EPAM and AstraZeneca discussed how modern approaches extract value from legacy data for any data-driven enterprise at the Data Innovation Summit 2026.
Watch the full session to explore:
- Transition from FAIR Data to AI-Ready Data
- Types of Legacy Data
- Three real use cases illustrating methods from the scientific industry
- The future of legacy data
Success comes from combining strong domain expertise with data and technology capabilities, creating a real competitive advantage for organizations ready to transform. Watch the full session:
Meet the Speakers
