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The data doom loop- Why big corporations are failing at data management

Despite significant investments in data governance and infrastructure modernization, many organizations struggle to efficiently serve high-quality data and adapt to the increasing pressures of effective data use in the era of LLMs. This paper introduces the concept of the “data doom loop,” a negative reinforcing cycle that leads to complex data environments frustrating all stakeholders.

To break this cycle, we propose the supergraph architecture, a new approach to enterprise data management. This centralized data access service fundamentally alters the relationship between data producers and consumers, potentially reducing data management costs by up to two-thirds. Key features include metadata-driven operations, autogenerated APIs, domain-based CI/CD, and AI awareness.

By implementing this architecture, organizations can expect faster time-to-market for data products, lower costs, improved compliance, and seamless integrations with various data tools, ultimately creating a flywheel of continuous data improvement.

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