This whitepaper shows how manufacturers can turn fragmented, high-volume IT/OT data into value with modern cloud data platforms. Traditional warehouses struggle with scale, formats, and speed; the fix is a Lakehouse on Azure/AWS (e.g., Databricks) that merges low-cost Data Lakes with warehouse reliability (Delta Lake), governance (Unity Catalog), and ML/AI tooling (Spark, MLflow). Outcomes: faster time-to-insight, lower storage/compute cost, fine-grained access, and real-time analytics. Pitfalls addressed: data integration, volume/diversity, data quality/management, and stakeholder speed. Proof points include BI setup, per-workpiece energy/CO₂ tracking, automotive anomaly detection, and energy-sector Lakehouse migration. The future: intelligent, sustainable, service-oriented manufacturing.

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