Modern Data Stack for Generative AI Integration

This white paper outlines the concept of a Modern Data Stack and its evolution in the context of Generative AI. It begins by defining the Modern Data Stack, which manages the flow of data from various sources through ingestion, storage, processing, and ultimately to analysis and output. The document emphasizes the importance of critical services such as data discovery, governance, observability, entitlements, and security within this framework. It discusses the business goals associated with implementing a Modern Data Stack, including enabling digital transformation, fostering a data-driven culture, and addressing challenges like data silos. The paper also highlights the need for a comprehensive approach to data management that integrates Generative AI, suggesting that the existing architecture must evolve to accommodate new functionalities such as Large Language Models (LLMs) and self-service business intelligence outputs. The document concludes by advocating for a broader understanding of data governance and management processes in the age of AI.