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Over the last few years, many organizations have moved toward lakehouse architecture—combining the flexibility of data lakes with the performance of data warehouses. The promise? Unified access, scalable analytics, and AI-ready data. But for many data leaders, the reality has been disappointing: slow time-to-value, mounting technical debt, and pressure from the business to “show results.” In some cases, data leaders don’t stay in the role long enough to see the fruit of their labour. So…