The long-term success of an AI model is directly correlated to the quality of the data used to power it. Across the AI data pipeline, workloads vary in intensity and data types, and object sizes can fluctuate. Efficiently managing data throughout the AI data pipeline is essential to ensuring AI initiatives remain cost-effective and technically feasible.