Optimised Architectures – Designing Storage Architectures for Big Data and AI/ML Workloads

A thriving enterprise data economy is built on three imperatives: capture everything, manage it efficiently, and leverage its potential. Big data and AI/ML workloads necessitate the ability to process and analyse massive volumes of data, both structured and unstructured. Enterprises must reconsider numerous issues around data management, current and future storage capacity. This white paper considers hybrid cloud and storage architectures for enterprises seeking scalable and cost-effective IT infrastructure appropriate for big data and AI/ML workloads.