Data Tech 2026

AI agents are only as effective as the data they can securely access and accurately interpret. As organizations implement agent-based workflows, challenges like fragmented, inconsistent, ungoverned, and contextless data often hinder progress, reduce trust, and increase compliance risks. This session highlights the importance of the “Context Data Product”, a foundational element in building a Trusted Data Spine for AI. This robust, enterprise-grade data foundation empowers agents, analytics, and automation by ensuring data is contextual, reliable, and actionable.

With so many ambiguous definitions of data products ranging from dashboards and pipelines to datasets and APIs, organizations risk misallocating resources and missing out on adoption. In this session, we will demystify what a real data product is, break down its essential components, and highlight how both a Context Data Product and a data product mindset can drive tangible business results that extend beyond technical implementation. Whether you’re a data leader or practitioner, you’ll gain clear, actionable strategies for building effective data operating models and leave with a practical framework ready to adapt to your own environment.