13. Advanced Data Architecture, Review All , Data Architecture Principles and Enterprise Frameworks скачать в хорошем качестве

13. Advanced Data Architecture, Review All , Data Architecture Principles and Enterprise Frameworks

These sources primarily cover topics in advanced data architecture, focusing heavily on both data governance and security and the principles of Agentic AI. One document details the security and ethical requirements for AI, including limitations like knowledge cutoffs and the crucial role of Prompt Engineering and the Retrieval Augmented Generation (RAG) framework components. Concurrently, other documents address complex data modeling approaches, discussing the structure and drawbacks of data warehousing methods like the Kimball model and Data Vault architecture, including the use of Hubs, Links, and Satellites. Furthermore, the content stresses the absolute necessity of data governance for any modern data architecture to prevent failures, outlining specific security measures such as transport and application-layer encryption, firewalls, and robust role-based access control (RBAC) mechanisms for user authentication. Finally, the sources touch upon data ingestion challenges, like API schema drift and the complications arising from late-arriving data in business intelligence reporting. retrieved from to the University of Vaasa. Dr Amit Shukla