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Build real-time Power BI dashboards with Stream Analytics no code editor

This tutorial shows how you can use the Stream Analytics no code editor to compute aggregates on real time data streams and store it in Azure Synapse Analytics.

In this tutorial, you learn how to:

  • Deploy an event generator that sends data to your event hub
  • Create a Stream Analytics job using the no code editor
  • Review input data and schema
  • Select fields to group by and define aggregations like count
  • Configure Azure Synapse Analytics to which results will be written
  • Run the Stream Analytics job
  • Visualize data in Power BI

Prerequisites

Before you start, make sure you've completed the following steps:

  1. If you don't have an Azure subscription, create a free account.

  2. Deploy the TollApp event generator to Azure, use this link to Deploy TollApp Azure Template. Set the 'interval' parameter to 1. And use a new resource group for this step.

  3. Create an Azure Synapse Analytics workspace with a Dedicated SQL pool.

    Note

    If you'd like to build the real-time Power BI dashboard directly without capturing the data into database, you can skip step#3 and 4, then go to this guide to build real-time dashboard with Power BI dataset produced by Stream Analytics job.

  4. Create a table named carsummary using your Dedicated SQL pool. You can do it by running the following SQL script:

    CREATE TABLE carsummary   
    (  
        Make nvarchar(20),  
        CarCount int,
    	times datetime
    )
    WITH ( CLUSTERED COLUMNSTORE INDEX ) ;
    

Use no code editor to create a Stream Analytics job

  1. Locate the Resource Group in which the TollApp event generator was deployed.

  2. Select the Azure Event Hubs namespace.

  3. On the Event Hubs Namespace page, select Event Hubs under Entities on the left menu.

  4. Select entrystream instance.

    Screenshot showing the selection of the event hub.

  5. Go to Process data under Features section and then select start on the Start with blank canvas template.

    Screenshot showing the selection of the Start button on the Start with a blank canvas tile.

  6. Name your job carsummary and select Create.

    Screenshot of the New Stream Analytics job page.

  7. On the event hub configuration page, confirm the following settings, and then select Connect.

    1. For Consumer group, select Use existing, and then select Default.

    2. For Serialization type, confirm that JSON is selected.

    3. For Authentication mode, confirm that Connection String is used to connect to your event hub: Connection string.

      Screenshot of the configuration page for your event hub.

  8. Within few seconds, you see sample input data and the schema. You can choose to drop fields, rename fields or change data type if you want.

    Screenshot showing the preview of data in the event hub and the fields.

  9. Select Operations on the command bar and then select Group by.

    Screenshot showing the Operations menu with Group by selected on the command bar.

  10. Select the Group by tile on the canvas and connect it to the event hub tile.

    Screenshot showing the Group tile connected to the Event Hubs tile.

  11. Configure the Group by tile by specifying:

    1. Aggregation as Count.

    2. Field as Make which is a nested field inside CarModel.

    3. Select Add.

      Screenshot of the Aggregations setting in the Group by configuration page.

    4. In the Settings section:

      1. For Group aggregations by, select Make.

      2. For Time window, confirm that the value is set to Tumbling.

      3. For Duration, enter 3 minutes

      4. Select Done at the bottom of the page.

        Screenshot of the Group by configuration page.

  12. Select Group by, and notice the grouped data in the Data preview tab at the bottom of the page.

    Screenshot that shows the Data Preview tab for the Group by operation.

  13. On the command bar, select Operations and then Manage fields.

  14. Connect Group by and Manage fields tiles.

  15. On the Manage fields page, follow these steps:

    1. Add the Make field as shown in the following image, and then select Add.

      Screenshot showing the addition of the Make field.

    2. Select Add button.

      Screenshot showing the Add button on the Manage fields page.

  16. Select Add all fields on the Manage fields configuration page.

    Screenshot of the Manage fields page.

  17. Select ... next to the fields, and select Edit to rename them.

    • COUNT_make to CarCount

    • Window_End_Time to times

      Screenshot of the Manage fields page with the fields renamed.

  18. Select Done on the Manage fields page. The Manage fields page should look as shown in the following image.

    Screenshot of the Manage fields page with three fields.

  19. Select Manage fields tile, and see the data flowing into the operation in the Data preview tab at the bottom of the page.

    Screenshot that shows the Data Preview tab for the Managed Fields operation.

  20. On the command bar, select Outputs, and then select Synapse.

    Screenshot of command bar with Outputs, Synapse selected.

  21. Connect the Synapse tile to the Manage fields tile on your canvas.

  22. On the Synapse settings page, follow these steps:

    1. If the Job storage account isn't already set, select the Azure Data Lake Storage account in the resource group. It's the storage account that is used by Synapse SQL to load data into your data warehouse.

      Screenshot that shows the Synapse with selection of storage account.

    2. Select the Azure subscription where your Azure Synapse Analytics is located.

    3. Select the database of the Dedicated SQL pool that you used to create the carsummary table in the previous section.

    4. Enter username and password to authenticate.

    5. Enter table name as carsummary.

    6. Select Connect. You see sample results that will be written to your Synapse SQL table.

      Screenshot of the Synapse tile settings.

  23. Select Synapse tile and see the Data preview tab at the bottom of the page. You see the data flowing into the dedicated SQL pool.

    Screenshot that shows Data Preview for the Synapse tile.

  24. Select Save in the top ribbon to save your job and then select Start. Screenshot that shows the Start button selected on the command bar.

  25. On the Start Stream Analytics Job page, select Start to run your job.

    Screenshot of the Start Stream Analytics Job page.

  26. You then see a list of all Stream Analytics jobs created using the no code editor. And within two minutes, your job goes to a Running state. Select the Refresh button on the page to see the status changing from Created -> Starting -> Running.

    Screenshot showing the list of jobs.

Create a Power BI visualization

  1. Download the latest version of Power BI desktop.

  2. Use the Power BI connector for Azure Synapse SQL.

    Screenshot that shows the Power BI Desktop with Azure and Synapse Analytics SQL selected.

  3. Connect to your database with DirectQuery, and use this query to fetch data from your database

    SELECT [Make],[CarCount],[times]
    FROM [dbo].[carsummary]
    WHERE times >= DATEADD(day, -1, GETDATE())
    

    Screenshot that shows the configuration of Power BI Destop to connect to Azure Synapse SQL Database.

    Switch to Database tab, and enter your credentials (user name and password) to connect to the database and run the query.

  4. Select Load to load data into the Power BI.

  5. You can then create a line chart with

    • X-axis as times
    • Y-axis as CarCount
    • Legend as Make You'll then see a chart that can be published. You can configure automatic page refresh and set it to 3 minutes to get a real-time view. Screenshot of Power BI dashboard showing car summary data.

More option

Except the Azure Synapse SQL, you can also use the SQL Database as the no-code editor output to receive the streaming data. And then use Power BI connector to connect the SQL Database with your database with DirectQuery as well to build the real-time dashboard.

It's also a good option to build the real-time dashboard with your streaming data. For more information about the SQL Database output, see Transform and ingest to SQL Database.

Clean up resources

  1. Locate your Event Hubs instance and see the list of Stream Analytics jobs under Process Data section. Stop any jobs that are running.
  2. Go to the resource group you used while deploying the TollApp event generator.
  3. Select Delete resource group. Type the name of the resource group to confirm deletion.

Next steps

In this tutorial, you created a Stream Analytics job using the no code editor to define aggregations and write results to Azure Synapse Analytics. You then used the Power BI to build a real-time dashboard to see the results produced by the job.