Overview
In this learning path, the student is exposed to various ways to:
- Source streaming data sources into Microsoft Fabric.
- Use real time Eventstream in Microsoft Fabric.
- Query data in a KQL database in Microsoft Fabric.
- Create real time dashboards in Microsoft Fabric.
Why Choose KORNERSTONE
- Accredited, practitioner-led, expert certificate trainers to provide high quality training
- Official training material included
- Practical, scenario-based learning – focus on application, not just theory
- Excellent Passing Rate
Skills Covered
- Get started with Real-Time Intelligence in Microsoft Fabric
- Use real time event streams in Microsoft Fabric
- Query data in a KQL database in Microsoft Fabric
- Create Real-Time Dashboards with Microsoft Fabric
- Get started with Data Activator in Microsoft Fabric
Prerequisites
The student should be able to:
- Log in to the Azure portal.
- Explain and create resource groups.
- Understand the concept of streaming data.
- Familiar with Microsoft Fabric
- Introduction to Microsoft Fabric and Introduction to Real-Time Intelligence (RTI)
Target Audience
- Data Analyst
- Data Engineer
Course Curriculum
Module 1: Get started with Real-Time Intelligence in Microsoft Fabric
Analysis of real-time data streams is a critical capability for any modern data analytics solution. You can use the Real-Time Intelligence capabilities of Microsoft Fabric to ingest, query, and process streams of data.
Learning objectives
In this module, you’ll learn how to:
- Describe Real-Time Intelligence in Microsoft Fabric.
- Create eventhouse databases and tables using KQL database.
- Describe Real-Time hub in Microsoft Fabric.
- Use KQL to query tables and create querysets.
Module 2: Use real time event streams in Microsoft Fabric
This module is an introduction to the Microsoft Fabric Eventstream within Real-Time Intelligence (RTI).
Learning objectives
After completing this module, you’ll be able to:
- Establish source and destinations in Eventstream.
- View the data in-flight in eventstream items.
- Capture, transform, and route data using Eventstream.
Module 3: Query data in a KQL database in Microsoft Fabric
This tutorial provides a brief introduction to KQL (Kusto Query Language) queries using Querysets and the major differences between KQL and T-SQL when using Querysets.
Learning objectives
After completing this module, you’ll be able to:
- Use basic syntax and of Kusto Query Language (KQL).
- Understand the basics of the Queryset canvas.
- Describe how to execute T-SQL queries in the Queryset canvas.
- Describe how to convert T-SQL queries into KQL queries.
Module 4: Create Real-Time Dashboards with Microsoft Fabric
In this module, you’ll explore the user-friendly Real-Time Dashboard in Microsoft Fabric. This dashboard offers an auto-refresh feature for data, supports parameterization, and allows for a multi-page dashboarding experience without requiring any coding. It also integrates with Copilot for managing underlying query sets. This creates a seamless and efficient user experience.
Learning objectives
By the end of this module, you’re able to:
- Create a Real-Time Dashboard in Microsoft Fabric.
- Understand some of its advanced features.
- Apply some best practices for effective use.
- Have hands-on experience in a lab exercise.
Module 5: Get started with Data Activator in Microsoft Fabric
Use Data Activator in Microsoft Fabric to easily monitor and take action on your data.
Learning objectives
After completing this module, you’ll be able to:
- Understand Data Activator.
- Understand triggers, conditions, and actions in Data Activator.
- Get data from Power BI Reports and EventStreams with Data Activator.
- Assign data and create triggers in Data Activator.
- Interact with Real-Time Intelligence.
Dates & Locations
October 20, 2026
Exam & Certification
To earn this Microsoft Applied Skills credential, learners demonstrate the ability to implement a Real-Time Intelligence solution in Microsoft Fabric, including:
- Preparing a Real-Time Analytics environment
- Creating and loading data from external sources
- Loading and processing streaming data by using Eventstreams
- Exploring and manipulating data
- Visualizing and exporting data
Candidates for this credential should be familiar with data transformation, exploratory analytics, and real-time dashboards. They should also be proficient in KQL.
