Start: Q3 2024
Publication: Q4 2024/Q1 2025
Region: Global
Preparing and Delivering Data for AI: Adoption Trends, Requirements, and Best Practices
Artificial intelligence initiatives put a lot of pressure on enterprise data teams. These teams, already busy managing structured tables for traditional analytics, must learn new tools, techniques, and processes to prepare multi-structured datasets for AI/ML and now GenAI models. They also must extend their data governance programs to minimize risks related to accuracy, privacy, and explainability.
This survey-based report assesses the status of data delivery across hybrid and cloud or multi-cloud environments to support AI. It examines the objectives, challenges, requirements, use cases, and best practices of both large and small companies across the globe. It explores how various data stakeholders integrate, store, master, catalog, and observe the various datasets that feed AI-driven applications—and how they support the lifecycle of AI models.
Readers will learn: