/cdx → Azure, Microsoft Fabric → data-science-ai-workflow
Data Science + AI Workflow
Part of the scenario: Unify your Data Platform
Fabric Data Science Agent transforms Zava’s raw customer and operational data into predictive, AI-driven insights by automating the "explore-model-predict-act" cycle. It eliminates manual complexity by leveraging Copilot-powered notebooks, unified Lakehouse data, and MLflow for end-to-end model lifecycle management. By combining scalable Spark processing with AI-assisted code generation and advanced models like LightGBM, it enables rapid churn prediction, customer segmentation, and personalized recommendations—empowering teams to proactively improve retention, optimize revenue strategies. Runs in a live demo tenant with realistic data — you try the real thing, not a slide deck.
More from Azure, Microsoft Fabric
3 related360° Customer Insights
Fabric Customer Intelligence Agent transforms Zava’s fragmented customer data into a unified, 360° insight engine by automating the "unify-segment-analyze-act" cycle. It eliminates blind spots by combining multi-source data into a single customer view using zero-copy architecture and advanced segmentation models. By integrating Fabric Data Agent with Copilot Studio, it enables natural language access to deep customer insights.
AI Agents for Smarter Operations
Fabric AI Operations Agent transforms Zava’s reactive operations into an intelligent, autonomous decision engine by orchestrating the "observe-analyze-decide-act" cycle across multiple AI agents. It eliminates operational inefficiencies by unifying data access through the Fabric Data Agent and enabling natural language-driven insights via Copilot. By coordinating specialized agents (Sales, Product, and Analyst) through Azure AI Foundry, it delivers real-time recommendations—such as inventory reallocation and promotion planning—empowering business users to proactively optimize operations.
Business Analysis with Power BI + Copilot
Fabric Copilot Analytics Agent transforms Zava’s fragmented data landscape into a unified, insight-driven decision engine by automating the "ingest-analyze-visualize-act" cycle. It eliminates data silos by leveraging a lake-centric architecture with Direct Lake mode, enabling real-time, high-performance analytics without duplication. By combining Power BI Copilot and Smart Narratives, it accelerates insight generation, identifies churn drivers, and empowers business users to take proactive actions that improve customer experience and operational performance.