Assembling your AI data strategy
Blog post from Starburst
The rise of AI presents significant opportunities for companies, necessitating the development of an AI data strategy that aligns with business needs and leverages the right data architecture. A successful AI data strategy integrates fast and flexible data access through technologies like the data lakehouse, which combines the analytics capabilities of a data warehouse with the flexibility of a data lake, forming a strong foundation for AI initiatives. This strategy involves three main pillars: ensuring data access across various platforms, fostering collaboration through data products that simplify data sharing, and implementing robust governance to maintain data quality and compliance. The Icehouse architecture, which combines the Iceberg open table format with the Trino SQL query engine, offers a scalable solution for handling AI data needs, supporting decentralized access while allowing for centralized processing of critical workloads. Starburst's Icehouse architecture enhances AI data strategies by providing a unified framework for data access, collaboration, and governance, integrating seamlessly with existing infrastructures to support evolving AI and analytics demands.