In today’s world, business intelligence (BI) has made a major impact by establishing a market for itself.
BI has helped manage our data to make it easily accessible and analyzed so that decision-makers can come to conclusions quickly and easily.
To give you some context, 75% of the global workforce uses BI regularly.
But the problem is that many are still unaware of some of the advanced features BI offers to help their business scale exponentially. Today, we will share those Advance Features of BI with you that not only helps save time but will let you use your data in hand with better clarity.
1. Natural Language Q & A Question Box
The Q&A visual in Power BI reports
2. Azure Machine Learning Integration
3. Custom Visual Development with R and Python Script
While Power BI supports numerous standard data visualizations out of the box, it’s also possible to make our own with custom data visualizations. By adding open-source data- viz libraries from R and Python, judges can produce largely customizable visualizations to add to their coming Power BI report.
An R script is a text file containing (nearly) the same commands that you would enter on the command line of R.(nearly) refers to the fact that if you’re using sink() to shoot the output to a file, you’ll have to enclose some commands in print() to get the same output as on the command line.
The Power BI services supports viewing and interacting with illustrations created with R scripts. Illustrations created with R scripts, generally called R illustrations, can present advanced data shaping and analytics similar to forecasting, using R’s rich analytics and visualization power.
A Python script is a pack of commands in a file designed to be executed like a program. The file can contain functions and import colorful modules, but the script must be run within a Python interactive shell or through the command line to achieve a specific task.
Using Python in Power BI, we can extend the normal capabilities of the tool and enhance the way Power BI works. We can perform external data analysis using frameworks like Pandas, run external Python scripts from Power BI, produce and manipulate datasets, and produce visualizations using Python libraries.
4. Easy integration with Microsoft Power Suite {Power App, Power Automate, and Power Query}
Power BI is presently available as part of the Office 365 Enterprise E5 version.
Use Power Automate to merge Power BI with your favorite apps and services. With Power Automate, we create automated workflows to get notifications, synchronize files, collect data, and more.
In Power BI Desktop, On the Insert tab, select Power Automate (preview) in the Power Platform section. Once you choose the visual, it automatically gets added to your current report runner with getting started instructions.
With Microsoft Power Automate, you can automate exporting and distributing Power BI reports to various formats and scripts. In this composition, you create your inflow from scrape. You use the Import to train for Power BI Reports action to automatically distribute a Power BI report via email.
Power BI and PowerApps are crucial parts of the Microsoft Power Platform. Once you use these tools, you can enjoy lots of business openings.
With PowerApps and Power BI integration, we have a bigger picture and more significant perceptivity into our business while making the utmost of our information.
Power apps in Microsoft refer to the enhanced app development terrain that allows us to make robust and custom operations. It comes with an excellent collection of functions, data platforms, connectors, and services necessary for speeding up the entire app development process.
Power BI and PowerApps work in tandem, regardless of who initiates them. We can develop business processes that give crucial visualization and analysis once these two platforms are connected. We can also act immediately from anywhere and anytime, thanks to the apps we built using Power BI and PowerApps connectivity.
Step 1: Create a Data Set
Step 2: Create an Invoice Data Table
Step 3: Create a Power BI Report
Step 4: Publish the Power BI Report
Step 5: Calculate the Due Over Delays
Step 6: Switch to Report Edit Mode
Step 7: Choose the Fields
Step 8: Design the Application
Step 9: Modify and Design the Default Gallery Layout
Step 10: Create the Item Controls
Step 11: Add a Screen for Email
Step 12: Add an Email Icon
Step 13: Name the Application
Power BI and PowerApps integration bring uniqueness to a business’s market. If we have the opportunity to create multi-faceted business applications, we can efficiently meet all our business requirements. We also have the chance to shape the future of our business.
5. Predictive Analysis
Predictive analysis is a proficiency to see what will happen in the future. The predictive analytics model uses applied mathematics techniques with evolving technologies, like computing and Machine Learning to create correct predictions.
The predictive analysis answer uses current and historical facts, events, or patterns in historical and transactional knowledge.
Power BI element Auto ML automates machine learning model creation so that users will build high-quality predictive models.
Data visualization with Artificial Intelligence reflects the main elements of our data forcing predictions through our machine learning models.
Predictive analytics could be challenging, requiring a spread of study techniques and analytical capabilities. However, we can summarize the predictive analytics world in four straightforward steps.
As per Gartner’s report, by 2020, businesses using BI have an increase in profits compared to those not using BI. Over the years, Power BI has cemented itself as a business intelligence and reportage tool that enables users to form intuitive reports. These advanced features make BI even more robust and flexible. You get more options for reporting and sharing, along with various elements to tailor solutions to precise needs. So, explore the advantages of these advanced Power BI features and make the most of your business data seamlessly.
