Power BI for Real-time monitoring and decision-making
Power BI is a well-known business analytics service from Microsoft that allows you to interact with data to be able to come up with interactive visualizations. An excellent business solution, Microsoft Power BI allows users (both technical and non-technical) to generate comprehensive reports and dashboards without having to rely on IT resources.
Power BI offers a set of comprehensive tools and techniques to collect, prepare, visualize, and share data interactively across your organization in a completely secure way. The solution also allows you to create high-quality reports within no time.
But what if you have time-sensitive data (social media data, IoT telemetry, or other metrics that requires immediate action) that you wish to stream in real time for fast analysis and response?
This is where Power BI’s real-time streaming functionality comes in.
Power BI generally supports real-time streaming for the datasets such as Push Data, Streaming Datasets, and PubNub streaming datasets. In this post, we discuss more real-time streaming data in Power BI and how it helps in real-time monitoring and decision-making in the business.
Overview of Real-Time Streaming Data in Power BI
In Microsoft Power BI, a streaming dataset refers to a specific type of data you get via an API push. A streaming data set in Power BI is for a real-time dashboard and has various setups. This dataset can display data immediately upon receiving it without storing that data for the long term.
Unlike a DirectQuery connection report/dashboard, a real-time dashboard will automatically update the new data row as soon as it appears in the dataset.
The source of this new data row can be Stream Analytics, pushing through the REST API of Power BI or several other streaming services such as PubNub.
A real-time dataset in Power BI is primarily needed for situations where the change has to be seen as soon as it occurs. For instance, a real-time streaming dataset would be required in a place with a temperature sensor that monitors the temperature. A Power BI dashboard here will show the temperature changes in a line chart immediately as they happen.
Setting up Streaming Data Sets and Connecting to Streaming Sources
You can use three different ways to stream and set data into a dataset with the Power BI service.
REST APIs
Power BI REST APIs allow you to create and transfer data to push and stream datasets.
However, using the Power BI REST API for setting up streaming datasets does not always mean the Power Automate, as you can call the API using any other application as well.
Push Datasets
Here you need to select either the Streaming dataset or the PubNub dataset in Power BI. It is important to note that Push Datasets are similar to Streaming Datasets except that they can store data for historical analysis.
You can also select the streaming dataset type of API here and configure the exact values you want to stream to get a Push URL, post which you can Create an application that pushes the data using this Push URL.
Stream Analytics
Azure Stream Analytics refers to the data streaming service of Microsoft Azure and can be used for Power BI and many other tools and services in Microsoft toolset. It makes use of the REST APIs to create its output data stream.
Creating Real-Time Dashboards for Monitoring and Decision-Making
Creating a real-time dashboard for monitoring and decision-making with Microsoft Power BI is easy when tools such as Power Automate are used in the process.
Below are some examples of where you can use real-time monitoring and decision-making with Power BI.
- IoT devices- sensors or anything with a constant flow of data
- Monitoring stock levels
- Collecting various survey responses and viewing feedback immediately
Best Practices for Real-Time Data Analysis In Power BI
Given below are some of the best practices for real-time data analysis in Power BI.
Take a Streaming-First Approach
Taking a streaming-first approach to data integration here means ensuring continuous and real-time collection of data.
This is primarily because batch data collection sometimes fails to attain real-time latencies and doesn’t guarantee up-to-date data.
Data Processing Should Operate Continuously
Make sure that real-time data movement and stream processing applications operate continuously, as the administrators of such solutions need to understand the exact status of data pipelines and be alerted of any issues on an immediate basis.
This kind of continuous validation of data movement coupled with real-time data monitoring can lead to better business outcomes in the long run.
Further, this type of data monitoring can lead to better control of data management, especially when looking for anomalies in aspects such as data formats and volumes to support reliable data flow.
Do Not Import Entire Data Sets but Only Necessary Fields and Tables
Ensure that the overall model is as narrow and lean as possible. This is simply because Microsoft Power BI works majorly on columnar indexes, which means longer and leaner tables perform better.
Further, when importing a large table, make sure to partition it and process multiple partitions in parallel.
To conclude, we have discussed real-time data monitoring, virtualization, and decision-making in Power BI. It is quite a powerful feature of Power BI as it allows users to connect as well as track IOT sensor values on the web or mobile, especially to visualize and monitor sensor data in real-time via mobile devices.
Real-time streaming in Power BI is a very useful and productive feature for users. Combined with a cloud-based architecture, it allows unlimited access to users.
If you are also looking to extend Power BI’s real-time monitoring and decision-making functionality across all business units, look no further than TRNDigital. As a certified Microsoft partner, TRN can help you conveniently set up your Power BI account and enables you to integrate and work seamlessly with this tool. Our Power BI experts have several years of experience working in the field.
Contact our experts today to learn more about real-time Power BI streaming and to clarify any queries.