What Your Lakehouse Needs to Power Agentic AI
Webinar Speaker: Donald Farmer, Research Fellow
Date: Thursday, March 26, 2026
Time: 12:00 p.m. PT / 3:00 p.m. ET
Organizations invest heavily in lakehouse architectures for good reason: it consolidates storage, governance, and compute in one place. However, a persistent gap remains. The analysts and business experts closest to the decisions often cannot access or shape that data without filing a ticket or waiting for data engineers. This bottleneck doesn't just slow down reporting—it undermines the trust, auditability, and governance that AI applications demand.
Agentic AI applications require clean, semantically rich, and well-governed data. When only highly technical users can prepare and validate this information, organizations struggle to build autonomous AI systems they can actually explain, audit, or trust. The data pipelines designed for yesterday's dashboards were simply not built for this new era of automation.
Join TDWI research fellow Donald Farmer, alongside industry experts from Databricks and Alteryx, for a strategic look at how leading organizations are closing this divide. We will discuss the opportunity to combine robust lakehouse infrastructure with accessible analytics platforms, enabling a broader range of users to contribute to the data stack without compromising the governance, performance, and cost disciplines required by IT.
In this webinar, we will explore:
Maximizing lakehouse investments: How pushdown execution keeps transformations and analytics inside the data platform, reducing data movement and compute costs while preserving established IT governance models.
Widening the contributor base: Empowering analysts through no-code interfaces to natively explore, transform, and act on data without engineering queues, expanding who can deliver value from existing infrastructure.
Building AI you can trust: Establishing a foundation for auditable and explainable Agentic AI through self-service access to governed data enriched with critical business context, logic, and calculations.
A practical path forward: Transitioning from ad hoc analysis toward automated, AI-driven decision-making without the need to rearchitect what already works.
Guest Speakers
Stephen Archut
Senior Director of Solutions Marketing
Alteryx
Stephen is Senior Director of Solutions Marketing at Alteryx, where he focuses on helping organizations unlock more value from their data infrastructure. With over 20 years in data and analytics enterprise software, he has led product and solutions marketing across both analytics platforms and data management, a combination that gives him a grounded perspective on where the needs of IT and business users intersect.
That dual background spans roles at Alteryx, Explorium, TIBCO, and IBM. Stephen understands both how IT teams build and govern data pipelines and how analysts actually need to work with that data and why closing that gap matters more now than ever.
Saurabh Shukla
Senior Specialist Solution Architect
Databricks
Saurabh Shukla is a Senior Specialist Solution Architect at Databricks. Databricks is a global data, analytics, and artificial intelligence company. Saurabh has over 15 years of experience and has successfully tackled real-world business challenges using analytics, big data solutions, and cutting-edge technologies in Machine Learning (ML) and Artificial Intelligence (AI).
At Databricks, Saurabh uses his expertise to architect robust data lakes, implement best practices for data management, and lead data teams toward pioneering solutions. He is passionate about developing advanced data applications that drive business value and innovation. Saurabh has gained broad industry knowledge spanning healthcare, retail, and finance, working with various organizations to harness the power of data. Saurabh holds a Master's degree in Data Science from IU Bloomington.
Donald Farmer