Self–Optimizing AI data systems: a systematic literature review of CQLE-Aware query optimization, Edge–cloud offloading, Cloud/HPC orchestration, Data–Centric MLOps, and RAG
Self-optimising data systems for AI are reviewed across five strands: learned query optimisation and approximate analytics, edge and IoT offloading, cloud and HPC orchestration, data-centric governance and MLOps, and retrieval-augmented generation. A search of six sources over 2020 to 2026 identified 1,261 records, of...