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A live dashboard is a performance tool used to analyze, track, and report on the company’s data in real time with the help of interactive visualizations. These real time dashboards are automatically updated and provide the user with instant access to critical data.
Jun 21, 2023 · Why Should You Create a Live Dashboard in Power BI? Choosing the Right Data Sources for Your Power BI Dashboard; Understanding Power BI’s Live Connection Feature; Step-by-Step Guide to Creating a Live Dashboard in Power BI; Adding Visualizations and Charts to Your Power BI Dashboard; Customizing Your Live Dashboard with Filters and Slicers
Dec 12, 2023 · What are live dashboards? Live dashboards offer real-time visual representations of your data. They often provide a comprehensive and interactive overview of an organization's data, allowing you to monitor, analyze, and respond to changes as they occur.
People also ask
What is a live dashboard?
What is a live dashboard in Power BI?
What is a live KPI dashboard?
Why should you use a live dashboard?
A live dashboard displays metrics and data visualizations in real-time. This enables teams and decision makers to react to changes in status and performance as quickly as possible. Live KPI dashboards are particularly useful in situations where important metrics are otherwise difficult to access, or when the team’s attention is focused on ...
- Overview
- Types of real-time semantic models
- Push data to semantic models
- Set up your real-time streaming semantic model in Power BI
- Create a streaming semantic model
- Example of real-time streaming in Power BI
- Questions and answers
- Automatic page refresh
- Related content
Power BI with real-time streaming helps you stream data and update dashboards in real time. Any visual or dashboard created in Power BI can display and update real-time data and visuals. The devices and sources of streaming data can be factory sensors, social media sources, service usage metrics, or many other time-sensitive data collectors or transmitters.
This article shows you how to set up and use real-time streaming semantic models in Power BI.
First, it's important to understand the types of real-time semantic models that are designed to display in tiles and dashboards, and how those semantic models differ.
The following three types of real-time semantic models are designed for display on real-time dashboards:
•Push semantic model
•Streaming semantic model
•PubNub streaming semantic model
This section explains how these semantic models differ from one another. Later sections describe how to push data into each of these semantic models.
This section describes how to create and push data into the three primary types of real-time semantic models that you can use in real-time streaming.
You can push data into a semantic model by using the following methods:
•The Power BI REST APIs
•The Power BI streaming semantic model UI
To get started with real-time streaming, you choose one of the following ways to consume streaming data in Power BI:
•Tiles with visuals from streaming data
•Semantic models created from streaming data that persist in Power BI
For either option, you need to set up streaming data in Power BI. To get your real-time streaming semantic model working in Power BI:
1.In either an existing or new dashboard, select Add a tile.
2.On the Add a tile page, select Custom Streaming Data, and then select Next.
There are three ways to create a real-time streaming data feed that Power BI can consume and visualize:
•Power BI REST API using a real-time streaming endpoint
•Azure Stream
•PubNub
Here's an example of how real-time streaming in Power BI works. This sample uses a publicly available stream from PubNub. Follow along with the example to see the value of real-time streaming for yourself.
1.In the Power BI service, select or create a new dashboard. At the top of the screen, select Edit > Add a tile.
2.On the Add a tile screen, select Custom Streaming Data, and then select Next.
3.On the Add a custom streaming data tile page, select Add streaming semantic model.
4.On the New streaming semantic model page, select PubNub, and then select Next.
5.On the next screen, enter a Semantic model name, enter the following values into the next two fields, and then select Next.
Here are some common questions and answers about real-time streaming in Power BI.
Can you use filters on push or streaming semantic models?
Streaming semantic models don't support filtering. For push semantic models, you can create a report, filter the report, and then pin the filtered visuals to a dashboard. However, there's no way to change the filter on the visual once it's on the dashboard.
You can pin the live report tile to the dashboard separately, and then you can change the filters. However, live report tiles won't update in real time as data is pushed in. You have to manually update the visual by selecting the Refresh icon at top right on the dashboard page.
When you apply filters to push semantic models that have DateTime fields with millisecond precision, equivalence operators aren't supported. Operators such as greater than > or less than < operate properly.
How do you see the latest value on push or streaming semantic models?
You can use automatic page refresh at a report page level to set a refresh interval for visuals that's only active when the page is being consumed. Automatic page refresh is available only for DirectQuery data sources. The minimum refresh interval depends on the type of workspace where the report is published and capacity admin settings for Premium workspaces.
For more information about automatic page refresh, see Automatic page refresh in Power BI.
•Overview of the Power BI REST API with real-time data
•Load data in a Power BI streaming semantic model and build a dataflows monitoring report with Power BI
A real-time dashboard is an interactive real-time data visualization that displays continually updated metrics. It incorporates data that is just seconds old, refreshes almost instantaneously, and can support many concurrent viewers at once.
Live Dashboards by Service. Dashboard samples for cloud-based and on premise services like Google Analytics, Salesforce, Facebook, Microsoft Excel, and many more.
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