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Microsoft

Real-Time Intelligence & Semantic Modeling

Microsoft via Coursera

Overview

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Deliver live, responsive analytics by combining real-time intelligence with advanced semantic modeling in Microsoft Fabric. This hands-on course guides you through streaming architecture and BI optimization so you can build scalable dashboards that support high-performance decision-making. You’ll write KQL queries with time-series windowing to power real-time dashboards and configure Eventstream to capture and route streaming data to destination sinks. You’ll design Eventhouse table schemas with retention policies to support compliance and performance needs. Moving into semantic modeling with Power BI, you’ll build star-schema models with correct relationships and hierarchies, write optimized DAX measures using iterators and time-intelligence functions, configure calculation groups with dynamic format strings, implement incremental refresh and aggregations, and use Performance Analyzer to resolve report bottlenecks. By the end of this course, you’ll be able to design real-time analytics solutions and production-grade semantic models that deliver fast, governed, and scalable BI experiences.

Syllabus

  • KQL Queries for Real-Time Analytics
    • Master KQL syntax for time-series analytics and connect queries to Power BI for real-time dashboards.
  • Real-Time Intelligence Overview and Eventstream Configuration
    • Learn the Real-Time Intelligence ecosystem and set up Eventstream to capture and route streaming data.
  • Designing Eventhouse Tables with Retention
    • Create Eventhouse tables optimized for time-series analytics with appropriate retention policies.
  • Star Schema Design and Field Parameters
    • Understand semantic models and build star-schema relationships with proper cardinality, hierarchies, and field parameters for user-driven analysis.
  • Iterators, Time Intelligence, and DAX Optimization
    • Master DAX patterns for complex calculations while understanding performance implications.
  • Creating Calculation Groups with Dynamic Formats
    • Build calculation groups that apply consistent time-intelligence patterns across all measures.
  • Incremental Refresh and Aggregations
    • Set up incremental refresh policies and aggregation tables to achieve sub-second query times on large data.
  • Report Performance Analysis and Optimization
    • Diagnose slow reports with Performance Analyzer and implement targeted optimizations.
  • Real-Time Dashboard & Semantic Model Project
    • Integrate all Long Course 4 skills to build and document a real-time dashboard with streaming data and an optimized semantic model.

Taught by

Microsoft

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