Data Products for AI: Making Enterprise Data Trustworthy and Usable
Webinar Speaker: Donald Farmer, Research Fellow
Date: Thursday, June 25, 2026
Time: 12:00 p.m. PT / 3:00 p.m. ET
Enterprises hold their most valuable operational data inside the ERP systems that run finance, supply chain, and manufacturing. As they turn to AI and advanced analytics, they want that data working in models for forecasting, planning, and day-to-day decisions. However, preparing data cleanly and at scale has proven harder than expected.
For decades, teams have built ETL and data pipelines to copy this data into separate systems for analysis. Those pipelines multiply, grow fragile, and cost more each year to maintain; the copied data often arrives without clear lineage, leaving no reliable way to trace its origin or audit how a figure was calculated. AI raises the stakes, because a model trained on ungoverned data can be a danger to the entire business.
Today, a different approach to the data foundation is taking hold: keep core business data where it lives, with shared governance, full lineage, and access control; meanwhile make it usable alongside cloud, IoT, and third-party sources without repeated copying.
Drawing on enterprise practice and TDWI research, this webinar examines what this new approach changes for analytics and AI, where it lowers cost, and which use cases it serves best, including forecasting, demand planning, and generative and agentic AI.
Donald Farmer, TDWI research fellow, and industry-leading experts from SAP, Databricks and NTT DATA will discuss how attendees can evaluate their current approach against the demands of AI, and how to ensure your best business data reaches the people and models who use it. Key takeaways:
- Why decades of extraction pipelines left organizations with cost and complexity, but little lineage or auditability
- How keeping core business data in place, under shared governance, changes the economics of analytics and AI
- What separates a governed, open data foundation from the self-service dashboards most teams run today
- Which AI and machine-learning use cases depend on access to trusted business data, from demand planning to generative applications
- How to judge readiness, and avoid lock-in, when modernizing the path from operational systems to analytics
Date: June 25, 2026
Time: 12:00 pm PT
Donald Farmer