Building AI You Can Trust: Driving Business Value with Data Quality, Observability, and Governance
Results of New TDWI Best Practices Research
Webinar Speaker: Fern Halper, TDWI VP Research, Senior Research Director for Advanced Analytics
Date: Thursday, December 12, 2024
Time: 9:00 a.m. PT / 12:00 p.m. ET
Recently, TDWI has observed that organizations are feeling a lot of pressure to implement AI and generative AI. Given this, AI needs to be trusted. Creating trusted AI systems starts with a commitment to data quality, observability, and governance—three important pillars that reinforce one another. However, TDWI research consistently finds that many organizations struggle to trust the quality of their data, a foundational issue that can hinder the success of AI projects. Observability can help by enabling teams to monitor data in real time and detect issues earlier. Governance is also a top priority in TDWI’s surveys, emphasizing the critical role it plays in defining policies, controlling data access, and ensuring compliance.
Woven together, data quality, observability, and governance can create a robust framework that supports trustworthy AI. This combination empowers organizations to develop AI systems that are not only accurate and actionable but also secure and compliant. Join this webinar featuring experts from Alation, Monte Carlo, and Databricks to discuss how these three core elements can help businesses derive maximum value from their AI initiatives, what this involves, and how to incorporate these concepts into your data ecosystem. Topics include:
- Trusted AI: What’s involved?
- Drilling into data quality, observability, and governance – what is different with AI?
- Building a data ecosystem that supports trusted AI
- Best practices for getting started
Date: December 12, 2024
Time: 9:00 am PT
Fern Halper, Ph.D.