Fabric Data Activator: Real-Time Data Feeds, Automated Alerts & Stock Intelligence
Proposed session for SQLBits 2026TL; DR
Retailers can use Microsoft Fabric to stream sales and stock data in real time, triggering automated alerts via Data Activator for rapid response to inventory changes and sales surges, driving smarter, faster retail operations.
Session Details
In today’s fast-paced retail environment, the ability to respond instantly to sales trends and stock fluctuations is critical for maintaining customer satisfaction and maximising revenue. This session explores how Microsoft Fabric’s Real-Time Intelligence (RTI) data capabilities empower retailers, amongst others, to monitor product sales and inventory levels, triggering automated alerts and actions through Data Activator.
We’ll dive into a practical retail scenario: imagine a chain of stores where every transaction and stock movement is streamed into Fabric’s Real-time Hub. Using Event Streams and Event House databases, data is ingested and processed at scale, blending both live and historical feeds with SQL and KQL. Data Activator then monitors these feeds for critical thresholds such as sudden spikes in sales or low stock levels and automatically generates alerts to store managers to trigger replenishment workflows.
We’ll dive into a practical retail scenario: imagine a chain of stores where every transaction and stock movement is streamed into Fabric’s Real-time Hub. Using Event Streams and Event House databases, data is ingested and processed at scale, blending both live and historical feeds with SQL and KQL. Data Activator then monitors these feeds for critical thresholds such as sudden spikes in sales or low stock levels and automatically generates alerts to store managers to trigger replenishment workflows.
3 things you'll get out of this session
• How to architect real-time retail solutions using Microsoft Fabric.
• The role of Real-time Hub, Event Streams, and Data Activator in building responsive, intelligent systems.
• How to design alerting logic for sales surges and inventory drops.
• The business impact of real-time analytics and automation in retail operations.
Speakers
Paul Andrew's other proposed sessions for 2026
An Evolution of Cloud Data Architectures - Lambda, Kappa, Delta, Mesh & Fabric - 2026
An Introduction to Delta Lake and The Lakehouse - 2026
Building Near Real-time Data Solutions in Microsoft Azure & Fabric - 2026
Data & Community: An Amazing Network Of Peers Supporting Innovation & Growth - 2026
Data Modelling: The Lost Art of Turning Inputs into Insights - 2026
Designing & Delivering Data Products: From Mesh Principles to Data Fabric Automation - 2026
Fast-Track Your Lakehouse Build with a Metadata Framework - 2026
Microsoft Fabric Platform Governance - Where To Start - 2026
Paul Andrew's previous sessions
An Evolution of Data Architectures - Lambda, Kappa, Delta, Mesh & Fabric
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Building an Azure Data Analytics Platform End-to-End
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Creating a Metadata Driven Orchestration Framework Using Azure Data Integration Pipelines
We'll explore delivering this framework within an enterprise and consider an architect’s perspective on a wider platform of ingestion/transformation workloads with multiple batches and execution stages.
ETL in Azure Made Easy with Data Factory Data Flows
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Using Azure DevOps for Azure Data Factory
DevOps as a concept does not always translate to the technology when implemented. In this session we'll explore that problem when working with Azure Data Factory and what the different cloud only CI/CD options are.
Complex Azure Orchestration w Dynamic Data Factory Pipelines
If you have already mastered the basics of Azure Data Factory (ADF) and are now looking to advance your knowledge of the tool this is the session for you.
Building an End to End IoT Solution Using Pi Sensors & Azure
Demonstrating an end to end IoT solution providing real-time sensor data from a Raspberry Pi into an Azure IoT Hub, through Stream Analytics, then with outputs to Power BI and SQL DB. Learn how to build this simplified IoT solution from scratch.