Data operationalization is becoming crucial for enterprises as data is increasingly used in real-time decision-making. This involves creating 'digital twins' of data pipelines, which are living maps of data movement and dependencies, rather than copies of the data itself. This approach aims to reduce data replication, latency, and costs by interacting with data where it resides, supported by an intelligent orchestration layer that enables automation and resilience in evolving enterprise networks. AI
IMPACT This shift towards data operationalization and automation, driven by AI, could streamline how enterprises leverage data for real-time decision-making and system resilience.
RANK_REASON Article discusses trends and implications of data operationalization, framed as expert opinion from a CTO.
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