GenAI drives adoption of open data architecture

Generative AI (GenAI) is transforming industries by enhancing productivity and operational efficiencies, necessitating a robust data stack that enables high-quality data feeding into AI models. As demonstrated by JP Morgan Chase's initiative to use OpenAI's GPT model for an AI-powered assistant, even regulated sectors like banking are adopting GenAI to streamline processes and improve employee productivity. This trend underlines the importance of data discovery and open data architecture, which allow both on-premises and cloud workloads to support AI initiatives effectively. Starburst's open data lakehouse, powered by the Trino SQL query engine, facilitates this by offering scalable and discoverable access to distributed data. This approach avoids the constraints of traditional Enterprise Data Warehouses (EDWs) by using open-source technologies like Apache Iceberg, enabling organizations to maintain flexibility and control over their data. As more companies pivot toward a data-first strategy for AI, adopting an open data stack with strong data discovery capabilities becomes crucial for growth and supporting sophisticated AI initiatives.