Explore real-time analytics in Microsoft Fabric

In this exercise you’ll explore real-time analytics in Microsoft Fabric.

This lab will take approximately 25 minutes to complete.

Note: You’ll need a Microsoft Fabric license to complete this exercise. See Getting started with Fabric for details of how to enable a free Fabric trial license. You will need a Microsoft school or work account to do this. If you don’t have one, you can sign up for a trial of Microsoft Office 365 E3 or higher.

Create a workspace

Before working with data in Fabric, create a workspace with the Fabric trial enabled.

1. Sign into Microsoft Fabric at https://app.fabric.microsoft.com.
2. In the menu bar on the left, select Workspaces (the icon looks similar to 🗇).
3. Create a new workspace with a name of your choice, selecting a licensing mode in the Advanced section that includes Fabric capacity (Trial, Premium, or Fabric).

4. When your new workspace opens, it should be empty.

   

Create a KQL database

Now that you have a workspace, you can create a KQL database to store real-time data.

1. At the bottom left of the portal, switch to the Real Time Analytics experience.

   

   The real time analytics home page includes tiles to create commonly used assets for real-time data analyis

2. In the real time analytics home page, create a new KQL Database with a name of your choice.

   

   You will see a dashboard screen and then select the KQL Database button at the top.

   

   Once selected you will be given a New KQL Database dialog box where you will give your KQL Database a name.

   

   • name the database, in this scenario, it is: my_kql_db
   • click, Create

   After a minute or so, a new KQL database will be created:

   Currently, there are no tables in the database.

Create an eventstream

Eventstreams provide a scalable and flexible way to ingest real-time data from a streaming source.

1. In the menu bar on the left, select the Home page for the real-time analytics experience.

2. On the home page, select the tile to create a new Eventstream with a name of your choice.

   After a short time, the visual designer for your eventstream is displayed.

   

   The visual designer canvas shows a source that connects to your eventstream, which in turn is connected to a destination.

3. On the designer canvas, in the New source list for your source, select Sample data. Then in the Sample data pane, specify the name taxis and select the Yellow Taxi sample data (which represents data collected from taxi journeys). Then select Add.

4. Beneath the designer canvas, select the Data preview tab to preview the data being streamed from the source:

   

5. On the designer canvas, in the New destination list for your destination, select KQL database. Then in the KQL database pane, specify the destination name taxi-data and select your workspace and KQL database. Then select Create and configure.
6. In the Ingest data wizard, on the Destination page, select New table and enter the table name taxi-data. Then select Next: Source.
7. On the Source page, review the default data connection name, and then select Next: Schema.
8. On the Schema page, change the Data format from TXT to JSON, and view the preview to verify that this format results in multiple columns of data. Then select Next: Summary.
9. On the Summary page, wait for continuous ingestion to be established, and then select Close.

10. Verify that your completed eventstream looks like this:

    

Query real-time data in a KQL database

Your eventstream continuously populates a table in your KQL database, enabling you to query the real-time data.

1. In the menu hub on the left, select your KQL database (or select your workspace and find your KQL database there).

2. In the … menu for the taxi-data table (which has been created by your eventstream), select Query table > Records ingested in the last 24 hours.

   

3. View the results of the query, which should be a KQL query like this:

    ['taxi-data']
    | where ingestion_time() between (now(-1d) .. now())
   

   The results show all taxi records ingested from the streaming source in the last 24 hours.

4. Replace all of the KQL query code in the top half of the query editor with the following code:

    // This query returns the number of taxi pickups per hour
    ['taxi-data']
    | summarize PickupCount = count() by bin(todatetime(tpep_pickup_datetime), 1h)
   

5. Use the ▷ Run button to run the query and review the results, which show the number of taxi pickups for each hour.

Clean up resources

If you’ve finished exploring real-time analytics in Microsoft Fabric, you can delete the workspace you created for this exercise.

1. In the bar on the left, select the icon for your workspace to view all of the items it contains.
2. In the … menu on the toolbar, select Workspace settings.
3. In the Other section, select Remove this workspace.