Power BI Streaming Dataset Example: How to Update Visuals and Dashboards in Real-Time

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Real-time streaming in Power BI can revolutionize the way you update and visualize your data. With the ability to stream data in real-time, you can ensure that your visuals and dashboards are always up-to-date with the latest information. In this article, we will explore the different types of real-time semantic models and learn how to push data to these models. We will also guide you through the process of setting up your own real-time streaming semantic model in Power BI.

Types of real-time semantic models

Before we dive into the process of setting up a real-time streaming semantic model, let's first understand the different types of semantic models available in Power BI. These models allow you to define the structure and relationships of your data, making it easier to analyze and visualize.

Push semantic model

The push semantic model is one of the most common types of real-time semantic models used in Power BI. It allows you to push data directly into the model using various methods, such as Power BI REST APIs or the streaming semantic model UI. This type of model is ideal for scenarios where you need to update your visuals and dashboards in real-time.

Streaming semantic model

The streaming semantic model is another type of real-time semantic model in Power BI. It allows you to create a streaming dataset and push data into it using Power Automate or other data integration tools. This model is particularly useful when you have a continuous stream of data that needs to be visualized and analyzed in real-time.

Push data to semantic models

Once you have set up your real-time semantic model in Power BI, the next step is to push data into it. There are several methods you can use to accomplish this:

Use Power BI REST APIs to push data

Power BI REST APIs provide a flexible and powerful way to push data into your real-time semantic models. You can use APIs to send data in various formats, such as JSON or CSV, and update your visuals and dashboards in real-time.

Use the streaming semantic model UI to push data

If you prefer a user-friendly interface, you can use the streaming semantic model UI in Power BI to push data into your models. This allows you to easily map your data fields and preview the changes before updating your visuals and dashboards.

Use Azure Stream Analytics to push data

Azure Stream Analytics is another option for pushing data into your real-time semantic models. This powerful tool allows you to process and analyze streaming data from various sources, such as IoT devices or social media streams, and update your visuals and dashboards in real-time.

Use the Power BI REST API

The Power BI REST API provides a comprehensive set of endpoints for interacting with your real-time semantic models. You can use the API to create, update, and delete datasets, as well as push data into them. This gives you full control over your real-time streaming process.

Use PubNub

PubNub is a popular real-time messaging service that can be integrated with Power BI to push data into your semantic models. With PubNub, you can easily stream data from various sources and update your visuals and dashboards in real-time.

Set up your real-time streaming semantic model in Power BI

Now that you have an understanding of the different types of real-time semantic models and how to push data into them, let's walk through the process of setting up your own real-time streaming semantic model in Power BI.

Step 1: Create a new streaming dataset in Power BI

The first step is to create a new streaming dataset in Power BI. This dataset will serve as the foundation for your real-time streaming semantic model. To create a new streaming dataset, follow these steps:

Open Power BI and sign in to your account.
In the left navigation pane, click on 'Datasets'.
Click on the 'Create' button and select 'Streaming dataset'.
Choose the type of dataset you want to create and click on 'Next'.
Follow the on-screen instructions to define the schema and configure the dataset.
Click on 'Create' to create the streaming dataset.

Step 2: Create a dataflow

Once you have created the streaming dataset, the next step is to create a dataflow. A dataflow allows you to transform and prepare your data before pushing it into the streaming dataset. To create a dataflow, follow these steps:

In the left navigation pane, click on 'Dataflows'.
Click on the 'Create' button and select 'Dataflow'.
Choose the data source for your dataflow and click on 'Next'.
Configure the dataflow settings, such as the refresh schedule and data transformations.
Click on 'Create' to create the dataflow.

Step 3: Create a flow in Power Automate

Power Automate allows you to automate workflows and integrate different systems and services, including Power BI. To create a flow to push data into your streaming dataset, follow these steps:

Open Power Automate and sign in to your account.
Click on 'Create' and select 'Automated flow'.
Choose the trigger that will initiate the flow, such as a new record in a database or a new email.
Configure the actions to push data into your streaming dataset.
Click on 'Save' to save the flow.

Step 4: Create a Power BI Report

Now that you have set up your real-time streaming semantic model and connected it to your data source, you can create a Power BI report to visualize the data. To create a Power BI report, follow these steps:

Open Power BI and sign in to your account.
In the left navigation pane, click on 'Reports'.
Click on the 'Create' button and select 'Report'.
Select the streaming dataset as your data source.
Create visualizations and dashboards to present the real-time data.
Click on 'Save' to save the report.

Congratulations! You have successfully set up a real-time streaming semantic model in Power BI and created a Power BI report to visualize the real-time data.

Example of real-time streaming in Power BI

Let's walk through a real-world example of how real-time streaming in Power BI can be used. Imagine you are a sales manager for an e-commerce company, and you want to monitor the sales performance of your online store in real-time. By setting up a real-time streaming semantic model in Power BI, you can visualize key metrics, such as total sales, number of orders, and top-selling products, in real-time.

Using Power Automate, you can connect your e-commerce platform to Power BI and push sales data into the streaming dataset. As new orders are placed, the data will be automatically updated in Power BI, allowing you to monitor the sales performance in real-time. You can create visualizations and dashboards to track the performance over time and identify trends and patterns.

Conclusion

Real-time streaming in Power BI is a powerful feature that allows you to update visuals and dashboards in real-time. By setting up a real-time streaming semantic model and pushing data into it, you can ensure that your visuals and dashboards are always up-to-date with the latest information. Whether you are monitoring sales performance, tracking website analytics, or analyzing IoT data, real-time streaming in Power BI can provide valuable insights and enable faster decision-making.