Accelerate AI with a data lake analytics platform

As AI and data science continue to evolve, the focus has shifted from finding algorithms to effectively scaling applications and making outputs accessible. The rise of data products, which are curated datasets designed to create value for downstream consumers, plays a crucial role in this transition. These data products span both legacy and modern systems and are central to the concept of a data mesh, which decentralizes data ownership across business domains. To efficiently manage data in complex environments, a consumption layer is recommended to decouple end users from data sources, bridging legacy and modern systems while ensuring security through centralized governance. With decentralized access and a data lake as the center of gravity, organizations can economically scale large data volumes and maintain flexibility with open data formats like ORC, Parquet, and Avro. This approach allows for the seamless integration of emerging technologies and enhanced interoperability across the data ecosystem.