Power BI advanced Analytics: 10 Must-Know Features before you use it
Advanced Analytics and Power BI
Companies are usually filled up with mounds and mounds of data. There are available technologies that have transformed the way to work on with the information that is there at present. This has brought in novel ways and business trends in the market.
Advanced Analytics is mainly dependent on an independent data or content examination using complicated tools and ways that are entirely different from those of the conventional techniques. This ensures that companies would be able to uncover some vital cognizance, predictions, or even generate probable recommendations.
Advanced Analytics with Power BI can help many users out with getting some vital insights and even carry out data transformation procedures and solve company issues. Power BI Trend analysis indicates that when coupled with advanced analytics, it would help out companies to identify some key performance indicators in real-time. Companies would be able to drive businesses in a positive way driving more possibilities.
The following section would put some emphasis on the advanced analytics features present in Power BI. It would also contain some Power BI Features that come amalgamated with advanced analytics.
Advanced Analytics features in Power BI
Let us now have a look at some of the facts about the power BI that you should know coupled with advanced analytics features,
1. Quick Insights – This feature was introduced along with Microsoft Research with the advanced analytical algorithms. It provides users with a novel way to search up for insights from the company info. Quick Insights provides users increased visibility to these insights within a stipulated amount of time, all of that with just one click.
2. Ask your queries – This functionality can give the user the complete freedom to add a query button inside the report. This would also ensure that the users can execute random analysis along with report creation. The feature gives you the liberty to ask your queries in the natural language.
3. Integration with R – R is a language that is used widely when it comes to data miners and statisticians for the development of statistical software along with data analysis. Using R Connectors, users would be able to run scripts into the Power BI. The data that you receive post this would then be imported seamlessly into the Power BI Data model.
4. Intelligent App Suggestions –This is one of the most sophisticated models of this Advanced Analytics feature. It would assist the users with listing down the applications based on their overall popularity. It would also depend upon how relevant it is, what the content is related to it, and the total reviews of the users.
5. Azure Machine Learning Integration –Since this feature also involves integration with that of machine learning in the Power BI, it would help the users with the complete visualization of the results of the Machine Learning Algorithm. This can be done simply by just dragging and dropping and even connecting all the data modules.
6. Data Shaping user R –Integrating R with the Power Query editor would help the users to get the data, clean them out, and then execute the data shaping activity with only a few clicks. Users would even be made to perform advanced analytics of the data.
7. Segmentation and Cohort Analysis –This is one of the most popular and straightforward methods for exploring the data sets. It can combine or break data sets into one cluster. These clusters would then be compared for the identification of data set relationships. Some of the Power BI Tools that can assist the segmentation and cohort analysis. It would even help in creating a conjecture of the business data and understand all the business requirements for a review.
8. Data Analysis Expression –DAX can help users out with getting one or more data set values by calculating multiple data along with the existing one. These functions would then be calculated along with the formulas. Its functionality is similar to that of Microsoft Excel, but it does not contain any of the difficulties of rows and numbers.
9. Microsoft Azure Steam Analytics Integration –Integration of Power BI with Azure Machine Learning and Stream Analytics will ensure the users access the data in real-time. This combination will necessarily help companies with providing predictive intelligence to take dynamic steps.
10. Data Visualization in Power BI –Power BI helps organizations to find increased data visibility and therefore provide proper business insights. It will give the users alternatives, including pre-configured visualizations, customizing the current ones, and selecting from the complete list of displays from the gallery.
All of these advanced analytics features present in Power BI would help out the business users for data analyzing and also distribute vital insights for companies.
Computer Solutions East would help companies with appropriate data visualization and even helping companies with doing so. The expertise provided by the CSE team is best in class, and many clients have benefitted from the same.
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