In this discussion, our guests explore how modern data lake architectures, built on AWS, can help your organization adopt FAIR data principles—Findable, Accessible, Interoperable, and Reusable—to unlock the full potential of your scientific data.
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Scientific data is growing exponentially, yet much of it remains siloed, difficult to access, and underutilized. For life sciences organizations, the ability to store, manage, and share research data effectively can directly accelerate discovery and development.
Join PTP, AWS and Quilt Data for an insightful webinar exploring how modern data lake architectures, built on AWS, can help your organization adopt FAIR data principles—Findable, Accessible, Interoperable, and Reusable—to unlock the full potential of your scientific data.
In this session, you’ll learn:
- Why FAIR data principles are essential for maximizing the value of research data
- How AWS-powered data lakes enable secure, scalable, and compliant data storage and access
- Best practices for structuring and curating scientific data to make it actionable
- Real-world examples of life sciences organizations accelerating R&D through FAIR data strategies
Featured Speakers
Aaron Jeskey
Principal Cloud Architect | PTP
Aaron Jeskey leads cloud strategy and solution delivery at PTP, where he helps life sciences organizations harness the power of AWS to accelerate research and innovation. With over 15 years of experience in cloud architecture and IT operations, Aaron specializes in designing scalable, compliant, and AI-ready environments tailored to the unique needs of biotech and pharmaceutical companies. He is a trusted advisor to early-stage and enterprise clients alike, guiding them through cloud adoption, data modernization, and AI/ML enablement.
Kevin Moore
CEO | Quilt Data
Kevin is the CEO & Co-Founder of Quilt.bio, a platform that transforms scattered life sciences data into trusted, reusable packages.
Kevin brings deep expertise in large-scale system architecture to the life sciences world. Before founding Quilt, Kevin was a researcher at Oracle Labs specializing in high-performance database processing and hardware-software design. He holds a Ph.D. in Computer Science from the University of Wisconsin.
Quilt runs natively on AWS, bundling raw data, results, and metadata into secure, versioned assets with AI-powered search and seamless integration with tools like Benchling and Amazon HealthOmics. Kevin’s mission is simple: turn data chaos into scientific clarity, accelerating discovery while maintaining FAIR and GxP compliance.
Kevin brings deep expertise in large-scale system architecture to the life sciences world. Before founding Quilt, Kevin was a researcher at Oracle Labs specializing in high-performance database processing and hardware-software design. He holds a Ph.D. in Computer Science from the University of Wisconsin.
Quilt runs natively on AWS, bundling raw data, results, and metadata into secure, versioned assets with AI-powered search and seamless integration with tools like Benchling and Amazon HealthOmics. Kevin’s mission is simple: turn data chaos into scientific clarity, accelerating discovery while maintaining FAIR and GxP compliance.
