AI and Large Language Models (LLMs) promise transformative value, but only if the data behind them is accurate, secure, and governed. As organizations accelerate AI adoption, preparing data is no longer just about cataloging and cleansing – it’s about building trust, reducing risk, and ensuring compliance across the AI lifecycle.
Join Databricks, Accenture, and BigID for an in-depth discussion on how to align data preparation with the AI TRiSM (Trust, Risk, and Security Management) framework. Learn how to balance innovation with responsibility by discovering, classifying, and governing structured and unstructured data at scale, while protecting sensitive information and meeting regulatory demands.
Die wichtigsten Erkenntnisse:
- Understand how leaders apply AI TRiSM to strengthen trust and manage risk in AI adoption.
- Learn how the Databricks Data Intelligence Platform and DBRX support responsible GenAI with scalable data and model operations.
- See how BigID helps organizations detect AI-specific risk, validate training data, and enforce policy controls for secure and compliant AI.
- Explore real-world challenges in cataloging, classifying, and cleansing data – and how to overcome them.
- Gain practical methods to keep data strategies adaptable to evolving regulations and emerging AI technologies.
Join BigID, Databricks, and Accenture for actionable takeaways around how to be confident in preparing your data for use in AI and LLM technologies.
Redner:
- Raja Perumal, Director, ISV Technology Partners, Databricks
- Paul Barrett, Managing Director, Accenture
- Souvik Mukherjee, Managing Directo
- Stephen Gatchell, VP, Data & AI Strategy, BigID