As organizations modernize their data infrastructures, many discover that challenges remain: Data continues to be distributed across legacy and modern systems, as well as multiple cloud environments, yet semantics, the meaning of data, still needs to remain consistent across all consumers, from business intelligence dashboards to machine learning models and emerging AI-driven systems, to support today’s demanding use cases.
This whitepaper explores how modern organizations can address this challenge by establishing a semantics-first data architecture that separates data processing, data access, and data meaning. Such architectures are both efficient and coherent across highly complex infrastructures, enabling organizations to gain powerful results from modern use cases.
