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Tech Stories Tech Brief By HackerNoon · Saturday · 8 min

Building a Governed Customer 360 Data Product on Microsoft Fabric

This story was originally published on HackerNoon at: https://hackernoon.com/building-a-governed-customer-360-data-product-on-microsoft-fabric. Learn how to build an AI-ready Customer 360 data product with Microsoft Fabric, governed data layers, semantic models, and MCP tools. Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories. You can also check exclusive content about #microsoft-fabric, #enterprise-data-architecture, #customer-360-data-platform, #microsoft-onelake, #ai-ready-data-products, #data-governance, #power-bi-semantic-models, #fabric-iq, and more. This story was written by: @queryandconquer. Learn more about this writer by checking @queryandconquer's about page, and for more stories, please visit hackernoon.com. Microsoft Fabric enables building a Customer 360 data product that AI can use by following a layered architecture, including ingestion, curation, publication, consumption, and context layers. This approach ensures that AI systems have access to high-quality, governed data with explicit business context.

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This story was originally published on HackerNoon at: https://hackernoon.com/building-a-governed-customer-360-data-product-on-microsoft-fabric.
Learn how to build an AI-ready Customer 360 data product with Microsoft Fabric, governed data layers, semantic models, and MCP tools.
Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories. You can also check exclusive content about #microsoft-fabric, #enterprise-data-architecture, #customer-360-data-platform, #microsoft-onelake, #ai-ready-data-products, #data-governance, #power-bi-semantic-models, #fabric-iq, and more.

This story was written by: @queryandconquer. Learn more about this writer by checking @queryandconquer's about page, and for more stories, please visit hackernoon.com.

Microsoft Fabric enables building a Customer 360 data product that AI can use by following a layered architecture, including ingestion, curation, publication, consumption, and context layers. This approach ensures that AI systems have access to high-quality, governed data with explicit business context.

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