As labs scale, their data often grows without a clear structure or strategy. What begins as flexible can quickly become fragmented, with data spread across multiple tools, inconsistent formats, and limited alignment between wet lab, dry lab, and leadership teams.
Over time, this lack of shared governance and system design creates “data debt” that slows decision making, increases compliance risk, and reduces the long term value of scientific data.
In this webinar, we explore how to address these challenges by building a connected and structured data strategy, with practical insights and real examples from SciNote in action.
What you will learn:
Going beyond theory, this webinar shows what effective data strategy looks like in practice.
You will learn how to:
- Design data governance that supports science rather than slowing it down
- Build connected systems across wet lab, dry lab, and business teams
- Maintain workflow integrity and interoperability as your organization grows
- Address executive concerns around risk, compliance, and valuation
- Use structured ELN architecture to enable auditability and analytics
Hear directly from Elizabeth Deyett as she shares hands on experience building data strategy in a startup environment, including how scalable infrastructure was built, how workflows were connected, and how an ELN like SciNote supports clean data handoffs between teams.
You will gain a practical perspective on what works and what tends to break as labs scale, with insights relevant for executives, lab managers, and scientists aiming to improve data structure, reduce risk, and enable better collaboration.