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Module 1: Introduction to real-time intelligence
15 Lessons-
StartModule introduction
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StartWhat is real-time intelligence ?
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StartWhy real-time matters
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StartLatency vs freshness trade-offs
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StartBatch processing vs streaming
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StartWhat does Fabric Real-Time Intelligence provide ?
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StartWhat are events ?
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StartWhat are streams ?
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StartWhat is ingestion ?
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StartWhat is processing ?
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StartWhat are actions ?
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StartWhat is the real-time hub ?
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StartLab 1 video walkthroughs
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StartLab 1
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StartQuiz 1
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Module 2: Common real-time data sources
18 Lessons-
StartModule introduction
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StartEvent-driven vs request-driven systems
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StartMessage brokers and event streams
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StartAzure Event Hubs
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StartAzure IoT Hub
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StartUsing AMQP vs HTTP
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StartApache and Confluent Kafka
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StartRabbit MQ
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StartMessage queue comparisons
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StartDatabase CDC sources
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StartDatabase CES sources
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StartCDC vs CES comparison
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StartAzure and AWS storage events
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StartAzure and Fabric events
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StartHow Fabric connects to external sources
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StartLab 2 video walkthroughs
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StartLab 2
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StartQuiz 2
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Module 4: Event ingestion in Fabric
12 Lessons-
StartModule introduction
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StartWhat are eventstreams ?
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StartEvent processing inputs
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StartEvent processing outputs
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StartIngestion modes
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StartFiltering events
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StartMapping events
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StartRouting events
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StartDesigning Eventstream pipelines
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StartData quality in real-time
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StartWhat are event schema sets ?
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StartQuiz 4
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Module 5: Transforming real-time data
18 Lessons-
StartModule introduction
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StartFiltering
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StartManaging fields
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StartAggregating
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StartJoining with other streams
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StartGrouping
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StartApplying temporal windows
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StartTumbling
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StartSliding
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StartSession
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StartHopping
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StartSnapshot
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StartApplying union
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StartExpanding
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StartUsing custom SQL code
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StartLab 5 video walkthroughs
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StartLab 5
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StartQuiz 5
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Module 6: Querying and processing real-time data
12 Lessons-
StartModule introduction
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StartEventstream destinations
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StartKQL databases
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StartUsing visual exploration
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StartQuerying using KQL
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StartWhat are KQL Querysets ?
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StartJoining using KQL
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StartQuerying using SQL
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StartJoining using SQL
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StartWhen to use KQL or SQL
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StartHandling late-arriving or out-of-order data
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StartQuiz 6
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Module 7: Querying with KQL
16 Lessons-
StartModule introduction
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StartWhat is KQL ?
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StartCore concepts of KQL
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StartBasic query syntax
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StartFiltering
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StartProjections, extensions, and aliases
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StartWorking with time series
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StartAggregations
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StartJoins and lookups
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StartAdvanced operators
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StartFunctions in KQL
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StartAnomaly detection
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StartTrend analysis
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StartLab 7 video walkthroughs
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StartLab 7
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StartQuiz 7
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Module 8: Integrating analytics and visualization
14 Lessons-
StartModule introduction
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StartCreating real-time dashboards
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StartStreaming to lakehouses
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StartStreaming to warehouses
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StartBuilding alert-driven workflows
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StartThresholds
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StartAnomalies
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StartCreating Power BI reports on real-time data
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StartReal-time APIs and operational integration
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StartUsing Fabric Maps with Real-Time Intelligence
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StartBuilding digital twins
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StartLab 8 video walkthroughs
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StartLab 8
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StartQuiz 8
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Module 9: Acting on real-time events
13 Lessons-
StartModule introduction
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StartWhat is Fabric Activator ?
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StartUnderstanding objects and signals
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StartWhat are rules ?
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StartDetecting patterns
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StartTriggering actions
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StartIntegrating Power Automate
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StartIntegrating Logic Apps
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StartTriggering Teams, Emails, and Workflows
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StartMonitoring and managing triggers
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StartLab 9 video walkthroughs
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StartLab 9
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StartQuiz 9
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Module 10: Architecture and best practices
14 Lessons-
StartModule introduction
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StartDesigning for scale
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StartDesigning for reliability and resilience
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StartHandling backpressure
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StartHandling retries
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StartProviding fault tolerance
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StartReplay and Reprocessing
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StartSecurity and governance for pipelines
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StartGovernance and compliance
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StartCost considerations for streaming vs batch
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StartCost and performance optimization
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StartMonitoring and observability
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StartCommon pitfalls in real-time projects
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StartQuiz 10
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Module 14: Advanced concepts
13 Lessons-
StartModule introduction
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StartHybrid architectures
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StartData retention strategies
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StartScaling eventstreams
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StartKQL materialized views
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StartPartitioning strategies
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StartCross-database and cross-cluster queries
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StartUsing wildcards with union
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StartUsing special functions
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StartUsing update policies to transform data
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StartLab 14 video walkthroughs
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StartLab 14
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StartQuiz 14
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Module 15: Real-time AI integration
11 Lessons-
StartModule introduction
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StartIntegrating with machine learning
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StartAI-powered anomaly detection
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StartAI anomaly detector - how it works
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StartAI anomaly detector - available models
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StartAI anomaly detector - use cases
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StartAI anomaly detector - limitations
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StartIntegrating with MCP-based agents
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StartBuilding real-time RAG with Eventhouse
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StartUsing an Eventhouse as a vector database
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StartQuiz 15
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Module 16: Advanced integration and future trends
13 Lessons-
StartModule introduction
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StartIntegrating with Kafka Streams
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StartIntegrating with Flink
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StartIntegrating with Spark Structured Streaming
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StartIntegrating with Google Cloud Pub-Sub
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StartIntegrating with MQTT
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StartIntegrating KQL follower databases
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StartFabric RTI vs Azure Stream Analytics
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StartEmerging patterns for real-time
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StartDigital Twins
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StartEdge scenarios
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StartLab 16 video walkthroughs
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StartQuiz 16
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Mastering Real Time Intelligence in Microsoft Fabric®
Turn data into insights the moment it happens because yesterday’s data is already too late.
Course Summary
Do you need to master Real-Time Intelligence in Microsoft Fabric?
- Do you want to understand how data can be processed the moment it’s created — rather than hours or days later?
- Would you like to build systems that respond instantly to new information, such as customer actions, sensor readings, or transactions?
- Are you curious how tools in Microsoft Fabric can connect, process, and analyze data as it flows in real time?
- Do you want to design data pipelines that handle both live streaming and scheduled batch data with ease?
- Would you like to create dashboards that update automatically the moment new data arrives?
- Are you already experimenting with Microsoft Fabric’s real-time features and want to learn the right way to put them into practice?
- Or are you completely new to real-time data and want a clear, step-by-step introduction from an expert who makes complex ideas simple?
- Do you want to learn from an expert?
If any of this sounds like you, this course is the perfect place to start. You’ll get clear explanations, hands-on exercises, and short quizzes to make sure you not only understand the concepts—but can confidently apply them in real projects.
We encourage you to complete the practical exercises. We have tried to make this as easy as possible. The main thing you'll need is a trial (or real) Fabric account.
